Exploration on practice teaching reform of Photoelectric Image Processing course under applied transformation

NASA Astrophysics Data System (ADS)

Cao, Binfang; Li, Xiaoqin; Liu, Changqing; Li, Jianqi

2017-08-01

With the further applied transformation of local colleges, teachers are urgently needed to make corresponding changes in the teaching content and methods from different courses. The article discusses practice teaching reform of the Photoelectric Image Processing course in the Optoelectronic Information Science and Engineering major. The Digital Signal Processing (DSP） platform is introduced to the experimental teaching. It will mobilize and inspire students and also enhance their learning motivation and innovation through specific examples. The course via teaching practice process has become the most popular course among students, which will further drive students' enthusiasm and confidence to participate in all kinds of electronic competitions.

Nonuniform sampling theorems for random signals in the linear canonical transform domain

NASA Astrophysics Data System (ADS)

Shuiqing, Xu; Congmei, Jiang; Yi, Chai; Youqiang, Hu; Lei, Huang

2018-06-01

Nonuniform sampling can be encountered in various practical processes because of random events or poor timebase. The analysis and applications of the nonuniform sampling for deterministic signals related to the linear canonical transform (LCT) have been well considered and researched, but up to now no papers have been published regarding the various nonuniform sampling theorems for random signals related to the LCT. The aim of this article is to explore the nonuniform sampling and reconstruction of random signals associated with the LCT. First, some special nonuniform sampling models are briefly introduced. Second, based on these models, some reconstruction theorems for random signals from various nonuniform samples associated with the LCT have been derived. Finally, the simulation results are made to prove the accuracy of the sampling theorems. In addition, the latent real practices of the nonuniform sampling for random signals have been also discussed.

Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

NASA Astrophysics Data System (ADS)

Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

2016-05-01

This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

Laser pulse coded signal frequency measuring device based on DSP and CPLD

NASA Astrophysics Data System (ADS)

Zhang, Hai-bo; Cao, Li-hua; Geng, Ai-hui; Li, Yan; Guo, Ru-hai; Wang, Ting-feng

2011-06-01

Laser pulse code is an anti-jamming measures used in semi-active laser guided weapons. On account of the laser-guided signals adopting pulse coding mode and the weak signal processing, it need complex calculations in the frequency measurement process according to the laser pulse code signal time correlation to meet the request in optoelectronic countermeasures in semi-active laser guided weapons. To ensure accurately completing frequency measurement in a short time, it needed to carry out self-related process with the pulse arrival time series composed of pulse arrival time, calculate the signal repetition period, and then identify the letter type to achieve signal decoding from determining the time value, number and rank number in a signal cycle by Using CPLD and DSP for signal processing chip, designing a laser-guided signal frequency measurement in the pulse frequency measurement device, improving the signal processing capability through the appropriate software algorithms. In this article, we introduced the principle of frequency measurement of the device, described the hardware components of the device, the system works and software, analyzed the impact of some system factors on the accuracy of the measurement. The experimental results indicated that this system improve the accuracy of the measurement under the premise of volume, real-time, anti-interference, low power of the laser pulse frequency measuring device. The practicality of the design, reliability has been demonstrated from the experimental point of view.

Survey of Current Practice in the Fitting and Fine-Tuning of Common Signal-Processing Features in Hearing Aids for Adults.

PubMed

Anderson, Melinda C; Arehart, Kathryn H; Souza, Pamela E

2018-02-01

Current guidelines for adult hearing aid fittings recommend the use of a prescriptive fitting rationale with real-ear verification that considers the audiogram for the determination of frequency-specific gain and ratios for wide dynamic range compression. However, the guidelines lack recommendations for how other common signal-processing features (e.g., noise reduction, frequency lowering, directional microphones) should be considered during the provision of hearing aid fittings and fine-tunings for adult patients. The purpose of this survey was to identify how audiologists make clinical decisions regarding common signal-processing features for hearing aid provision in adults. An online survey was sent to audiologists across the United States. The 22 survey questions addressed four primary topics including demographics of the responding audiologists, factors affecting selection of hearing aid devices, the approaches used in the fitting of signal-processing features, and the strategies used in the fine-tuning of these features. A total of 251 audiologists who provide hearing aid fittings to adults completed the electronically distributed survey. The respondents worked in a variety of settings including private practice, physician offices, university clinics, and hospitals/medical centers. Data analysis was based on a qualitative analysis of the question responses. The survey results for each of the four topic areas (demographics, device selection, hearing aid fitting, and hearing aid fine-tuning) are summarized descriptively. Survey responses indicate that audiologists vary in the procedures they use in fitting and fine-tuning based on the specific feature, such that the approaches used for the fitting of frequency-specific gain differ from other types of features (i.e., compression time constants, frequency lowering parameters, noise reduction strength, directional microphones, feedback management). Audiologists commonly rely on prescriptive fitting formulas and probe microphone measures for the fitting of frequency-specific gain and rely on manufacturers' default settings and recommendations for both the initial fitting and the fine-tuning of signal-processing features other than frequency-specific gain. The survey results are consistent with a lack of published protocols and guidelines for fitting and adjusting signal-processing features beyond frequency-specific gain. To streamline current practice, a transparent evidence-based tool that enables clinicians to prescribe the setting of other features from individual patient characteristics would be desirable. American Academy of Audiology

Perceptions as Hypotheses

NASA Astrophysics Data System (ADS)

Gregory, R. L.

1980-07-01

Perceptions may be compared with hypotheses in science. The methods of acquiring scientific knowledge provide a working paradigm for investigating processes of perception. Much as the information channels of instruments, such as radio telescopes, transmit signals which are processed according to various assumptions to give useful data, so neural signals are processed to give data for perception. To understand perception, the signal codes and the stored knowledge or assumptions used for deriving perceptual hypotheses must be discovered. Systematic perceptual errors are important clues for appreciating signal channel limitations, and for discovering hypothesis-generating procedures. Although this distinction between `physiological' and `cognitive' aspects of perception may be logically clear, it is in practice surprisingly difficult to establish which are responsible even for clearly established phenomena such as the classical distortion illusions. Experimental results are presented, aimed at distinguishing between and discovering what happens when there is mismatch with the neural signal channel, and when neural signals are processed inappropriately for the current situation. This leads us to make some distinctions between perceptual and scientific hypotheses, which raise in a new form the problem: What are `objects'?

Sparse signal representation and its applications in ultrasonic NDE.

PubMed

Zhang, Guang-Ming; Zhang, Cheng-Zhong; Harvey, David M

2012-03-01

Many sparse signal representation (SSR) algorithms have been developed in the past decade. The advantages of SSR such as compact representations and super resolution lead to the state of the art performance of SSR for processing ultrasonic non-destructive evaluation (NDE) signals. Choosing a suitable SSR algorithm and designing an appropriate overcomplete dictionary is a key for success. After a brief review of sparse signal representation methods and the design of overcomplete dictionaries, this paper addresses the recent accomplishments of SSR for processing ultrasonic NDE signals. The advantages and limitations of SSR algorithms and various overcomplete dictionaries widely-used in ultrasonic NDE applications are explored in depth. Their performance improvement compared to conventional signal processing methods in many applications such as ultrasonic flaw detection and noise suppression, echo separation and echo estimation, and ultrasonic imaging is investigated. The challenging issues met in practical ultrasonic NDE applications for example the design of a good dictionary are discussed. Representative experimental results are presented for demonstration. Copyright © 2011 Elsevier B.V. All rights reserved.

Programmable optical processor chips: toward photonic RF filters with DSP-level flexibility and MHz-band selectivity

NASA Astrophysics Data System (ADS)

Xie, Yiwei; Geng, Zihan; Zhuang, Leimeng; Burla, Maurizio; Taddei, Caterina; Hoekman, Marcel; Leinse, Arne; Roeloffzen, Chris G. H.; Boller, Klaus-J.; Lowery, Arthur J.

2017-12-01

Integrated optical signal processors have been identified as a powerful engine for optical processing of microwave signals. They enable wideband and stable signal processing operations on miniaturized chips with ultimate control precision. As a promising application, such processors enables photonic implementations of reconfigurable radio frequency (RF) filters with wide design flexibility, large bandwidth, and high-frequency selectivity. This is a key technology for photonic-assisted RF front ends that opens a path to overcoming the bandwidth limitation of current digital electronics. Here, the recent progress of integrated optical signal processors for implementing such RF filters is reviewed. We highlight the use of a low-loss, high-index-contrast stoichiometric silicon nitride waveguide which promises to serve as a practical material platform for realizing high-performance optical signal processors and points toward photonic RF filters with digital signal processing (DSP)-level flexibility, hundreds-GHz bandwidth, MHz-band frequency selectivity, and full system integration on a chip scale.

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

Software algorithms for false alarm reduction in LWIR hyperspectral chemical agent detection

NASA Astrophysics Data System (ADS)

Manolakis, D.; Model, J.; Rossacci, M.; Zhang, D.; Ontiveros, E.; Pieper, M.; Seeley, J.; Weitz, D.

2008-04-01

The long-wave infrared (LWIR) hyperpectral sensing modality is one that is often used for the problem of detection and identification of chemical warfare agents (CWA) which apply to both military and civilian situations. The inherent nature and complexity of background clutter dictates a need for sophisticated and robust statistical models which are then used in the design of optimum signal processing algorithms that then provide the best exploitation of hyperspectral data to ultimately make decisions on the absence or presence of potentially harmful CWAs. This paper describes the basic elements of an automated signal processing pipeline developed at MIT Lincoln Laboratory. In addition to describing this signal processing architecture in detail, we briefly describe the key signal models that form the foundation of these algorithms as well as some spatial processing techniques used for false alarm mitigation. Finally, we apply this processing pipeline to real data measured by the Telops FIRST hyperspectral (FIRST) sensor to demonstrate its practical utility for the user community.

Method and apparatus for reconstructing in-cylinder pressure and correcting for signal decay

DOEpatents

Huang, Jian

2013-03-12

A method comprises steps for reconstructing in-cylinder pressure data from a vibration signal collected from a vibration sensor mounted on an engine component where it can generate a signal with a high signal-to-noise ratio, and correcting the vibration signal for errors introduced by vibration signal charge decay and sensor sensitivity. The correction factors are determined as a function of estimated motoring pressure and the measured vibration signal itself with each of these being associated with the same engine cycle. Accordingly, the method corrects for charge decay and changes in sensor sensitivity responsive to different engine conditions to allow greater accuracy in the reconstructed in-cylinder pressure data. An apparatus is also disclosed for practicing the disclosed method, comprising a vibration sensor, a data acquisition unit for receiving the vibration signal, a computer processing unit for processing the acquired signal and a controller for controlling the engine operation based on the reconstructed in-cylinder pressure.

Optical signal processing techniques and applications of optical phase modulation in high-speed communication systems

NASA Astrophysics Data System (ADS)

Deng, Ning

In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching the speed limitation of electronics. Thus, all-optical signal processing techniques are highly desirable to support the necessary optical switching functionalities in future ultrahigh-speed optical packet-switching networks. To cope with the wide use of optical phase-modulated signals, in the thesis, an all-optical logic for DPSK or PSK input signals is developed, for the first time. Based on four-wave mixing in semiconductor optical amplifier, the structure of the logic gate is simple, compact, and capable of supporting ultrafast operation. In addition to the general logic processing, a simple label recognition scheme, as a specific signal processing function, is proposed for phase-modulated label signals. The proposed scheme can recognize any incoming label pattern according to the local pattern, and is potentially capable of handling variable-length label patterns. Optical access network with multicast overlay and centralized light sources. In the arena of optical access networks, wavelength division multiplexing passive optical network (WDM-PON) is a promising technology to deliver high-speed data traffic. However, most of proposed WDM-PONs only support conventional point-to-point service, and cannot meet the requirement of increasing demand on broadcast and multicast service. In this thesis, a simple network upgrade is proposed based on the traditional PON architecture to support both point-to-point and multicast service. In addition, the two service signals are modulated on the same lightwave carrier. The upstream signal is also remodulated on the same carrier at the optical network unit, which can significantly relax the requirement on wavelength management at the network unit.

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Window and Overlap Processing Effects on Power Estimates from Spectra

NASA Astrophysics Data System (ADS)

Trethewey, M. W.

2000-03-01

Fast Fourier transform (FFT) spectral processing is based on the assumption of stationary ergodic data. In engineering practice, the assumption is often violated and non-stationary data processed. Data windows are commonly used to reduce leakage by decreasing the signal amplitudes near the boundaries of the discrete samples. With certain combinations of non-stationary signals and windows, the temporal weighting may attenuate important signal characteristics to adversely affect any subsequent processing. In other words, the window artificially reduces a significant section of the time signal. Consequently, spectra and overall power estimated from the affected samples are unreliable. FFT processing can be particularly problematic when the signal consists of randomly occurring transients superimposed on a more continuous signal. Overlap processing is commonly used in this situation to improve the estimates. However, the results again depend on the temporal character of the signal in relation to the window weighting. A worst-case scenario, a short-duration half sine pulse, is used to illustrate the relationship between overlap percentage and resulting power estimates. The power estimates are shown to depend on the temporal behaviour of the square of overlapped window segments. An analysis shows that power estimates may be obtained to within 0.27 dB for the following windows and overlap combinations: rectangular (0% overlap), Hanning (62.5% overlap), Hamming (60.35% overlap) and flat-top (82.25% overlap).

Practical remarks on the heart rate and saturation measurement methodology

NASA Astrophysics Data System (ADS)

Kowal, M.; Kubal, S.; Piotrowski, P.; Staniec, K.

2017-05-01

A surface reflection-based method for measuring heart rate and saturation has been introduced as one having a significant advantage over legacy methods in that it lends itself for use in special applications such as those where a person’s mobility is of prime importance (e.g. during a miner’s work) and excluding the use of traditional clips. Then, a complete ATmega1281-based microcontroller platform has been described for performing computational tasks of signal processing and wireless transmission. In the next section remarks have been provided regarding the basic signal processing rules beginning with raw voltage samples of converted optical signals, their acquisition, storage and smoothing. This chapter ends with practical remarks demonstrating an exponential dependence between the minimum measurable heart rate and the readout resolution at different sampling frequencies for different cases of averaging depth (in bits). The following section is devoted strictly to the heart rate and hemoglobin oxygenation (saturation) measurement with the use of the presented platform, referenced to measurements obtained with a stationary certified pulsoxymeter.

Design of High Quality Chemical XOR Gates with Noise Reduction.

PubMed

Wood, Mackenna L; Domanskyi, Sergii; Privman, Vladimir

2017-07-05

We describe a chemical XOR gate design that realizes gate-response function with filtering properties. Such gate-response function is flat (has small gradients) at and in the vicinity of all the four binary-input logic points, resulting in analog noise suppression. The gate functioning involves cross-reaction of the inputs represented by pairs of chemicals to produce a practically zero output when both are present and nearly equal. This cross-reaction processing step is also designed to result in filtering at low output intensities by canceling out the inputs if one of the latter has low intensity compared with the other. The remaining inputs, which were not reacted away, are processed to produce the output XOR signal by chemical steps that result in filtering at large output signal intensities. We analyze the tradeoff resulting from filtering, which involves loss of signal intensity. We also discuss practical aspects of realizations of such XOR gates. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomedical signal and image processing.

PubMed

Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

2011-01-01

Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

NASA Astrophysics Data System (ADS)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

Quantitative evaluation of photoplethysmographic artifact reduction for pulse oximetry

NASA Astrophysics Data System (ADS)

Hayes, Matthew J.; Smith, Peter R.

1999-01-01

Motion artefact corruption of pulse oximeter output, causing both measurement inaccuracies and false alarm conditions, is a primary restriction in the current clinical practice and future applications of this useful technique. Artefact reduction in photoplethysmography (PPG), and therefore by application in pulse oximetry, is demonstrated using a novel non-linear methodology recently proposed by the authors. The significance of these processed PPG signals for pulse oximetry measurement is discussed, with particular attention to the normalization inherent in the artefact reduction process. Quantitative experimental investigation of the performance of PPG artefact reduction is then utilized to evaluate this technology for application to pulse oximetry. While the successfully demonstrated reduction of severe artefacts may widen the applicability of all PPG technologies and decrease the occurrence of pulse oximeter false alarms, the observed reduction of slight artefacts suggests that many such effects may go unnoticed in clinical practice. The signal processing and output averaging used in most commercial oximeters can incorporate these artefact errors into the output, while masking the true PPG signal corruption. It is therefore suggested that PPG artefact reduction should be incorporated into conventional pulse oximetry measurement, even in the absence of end-user artefact problems.

Moving Triadic Gaze Intervention Into Practice: Measuring Clinician Attitude and Implementation Fidelity

PubMed Central

Olswang, Lesley B.; Greenslade, Kathryn; Pinder, Gay Lloyd; Dowden, Patricia; Madden, Jodi

2017-01-01

Purpose This research investigated a first step in implementing the dynamic assessment (DA) component of Triadic Gaze Intervention (Olswang, Feuerstein, Pinder, & Dowden, 2013; Olswang et al., 2014), an evidence-based protocol for teaching early signals of communication to young children with physical disabilities. Clinician attitudes about adopting external evidence into practice and implementation fidelity in DA protocol delivery were examined following training. Method Seven early intervention clinicians from multiple disciplines were trained to deliver the four essential elements of the DA protocol: (a) provide communication opportunity, (b) recognize child's potentially communicative signal, (c) shape child's signal toward triadic gaze, and (d) reinforce with play. Clinician attitude regarding adopting evidence into practice was measured at baseline and follow-up, with the Evidence-Based Practice Attitude Scale (Aarons, 2004). Implementation fidelity in delivering the protocol was measured for adherence (accuracy) and competence (quality) during trial implementation. Results Clinicians' attitudes about trying new evidence that at first was perceived as incongruent with their practice improved over the course of the research. Clinicians demonstrated strong adherence to the DA protocol; however, competence varied across clinicians and appeared related to child performance. Conclusions The results provided insight into moving Triadic Gaze Intervention into practice and yielded valuable information regarding the implementation process, with implications for future research. PMID:28525577

Transient high frequency signal estimation: A model-based processing approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, F.L.

1985-03-22

By utilizing the superposition property of linear systems a method of estimating the incident signal from reflective nondispersive data is developed. One of the basic merits of this approach is that, the reflections were removed by direct application of a Weiner type estimation algorithm, after the appropriate input was synthesized. The structure of the nondispersive signal model is well documented, and thus its' credence is established. The model is stated and more effort is devoted to practical methods of estimating the model parameters. Though a general approach was developed for obtaining the reflection weights, a simpler approach was employed here,more » since a fairly good reflection model is available. The technique essentially consists of calculating ratios of the autocorrelation function at lag zero and that lag where the incident and first reflection coincide. We initially performed our processing procedure on a measurement of a single signal. Multiple application of the processing procedure was required when we applied the reflection removal technique on a measurement containing information from the interaction of two physical phenomena. All processing was performed using SIG, an interactive signal processing package. One of the many consequences of using SIG was that repetitive operations were, for the most part, automated. A custom menu was designed to perform the deconvolution process.« less

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

An Introduction to Data Analysis in Asteroseismology

NASA Astrophysics Data System (ADS)

Campante, Tiago L.

A practical guide is presented to some of the main data analysis concepts and techniques employed contemporarily in the asteroseismic study of stars exhibiting solar-like oscillations. The subjects of digital signal processing and spectral analysis are introduced first. These concern the acquisition of continuous physical signals to be subsequently digitally analyzed. A number of specific concepts and techniques relevant to asteroseismology are then presented as we follow the typical workflow of the data analysis process, namely, the extraction of global asteroseismic parameters and individual mode parameters (also known as peak-bagging) from the oscillation spectrum.

Distributed optical signal processing for microwave photonics subsystems.

PubMed

Chew, Suen Xin; Nguyen, Linh; Yi, Xiaoke; Song, Shijie; Li, Liwei; Bian, Pengju; Minasian, Robert

2016-03-07

We propose and experimentally demonstrate a novel and practical microwave photonic system that is capable of executing cascaded signal processing functions comprising a microwave photonic bandpass filter and a phase shifter, while providing separate and independent control for each function. The experimental results demonstrate a single bandpass microwave photonic filter with a 3-dB bandwidth of 15 MHz and an out-of-band ratio of over 40 dB, together with a simultaneous RF phase tuning control of 0-215° with less than ± 3 dB filter shape variance.

The Partners for Change Outcome Management System: A Both/And System for Collaborative Practice.

PubMed

Sparks, Jacqueline A; Duncan, Barry L

2018-03-09

Systematic client feedback (SCF) is increasingly employed in mental health services worldwide. While research supports its efficacy over treatment as usual, clinicians, especially those who highly value relational practices, may be concerned that routine data collection detracts from clinical process. This article describes one SCF system, the Partners for Change Outcome Management System (PCOMS), along a normative (standardized measurement) to communicative (conversational) continuum, highlighting PCOMS' origins in everyday clinical practice. The authors contend that PCOMS represents "both/and," providing a valid signal of client progress while facilitating communicative process particularly prized by family therapists steeped in relational traditions. The article discusses application of PCOMS in systemic practice and describes how it actualizes time-honored family therapy approaches. The importance of giving voice to individualized client experience is emphasized. © 2018 Family Process Institute.

Signal detection by means of orthogonal decomposition

NASA Astrophysics Data System (ADS)

Hajdu, C. F.; Dabóczi, T.; Péceli, G.; Zamantzas, C.

2018-03-01

Matched filtering is a well-known method frequently used in digital signal processing to detect the presence of a pattern in a signal. In this paper, we suggest a time variant matched filter, which, unlike a regular matched filter, maintains a given alignment between the input signal and the template carrying the pattern, and can be realized recursively. We introduce a method to synchronize the two signals for presence detection, usable in case direct synchronization between the signal generator and the receiver is not possible or not practical. We then propose a way of realizing and extending the same filter by modifying a recursive spectral observer, which gives rise to orthogonal filter channels and also leads to another way to synchronize the two signals.

The Brassinosteroid Signaling Pathway—New Key Players and Interconnections with Other Signaling Networks Crucial for Plant Development and Stress Tolerance

PubMed Central

Gruszka, Damian

2013-01-01

Brassinosteroids (BRs) are a class of steroid hormones regulating a wide range of physiological processes during the plant life cycle from seed development to the modulation of flowering and senescence. The last decades, and recent years in particular, have witnessed a significant advance in the elucidation of the molecular mechanisms of BR signaling from perception by the transmembrane receptor complex to the regulation of transcription factors influencing expression of the target genes. Application of the new approaches shed light on the molecular functions of the key players regulating the BR signaling cascade and allowed identification of new factors. Recent studies clearly indicated that some of the components of BR signaling pathway act as multifunctional proteins involved in other signaling networks regulating diverse physiological processes, such as photomorphogenesis, cell death control, stomatal development, flowering, plant immunity to pathogens and metabolic responses to stress conditions, including salinity. Regulation of some of these processes is mediated through a crosstalk between BR signalosome and the signaling cascades of other hormones, including auxin, abscisic acid, ethylene and salicylic acid. Unravelling the complicated mechanisms of BR signaling and its interconnections with other molecular networks may be of great importance for future practical applications in agriculture. PMID:23615468

Compressed digital holography: from micro towards macro

NASA Astrophysics Data System (ADS)

Schretter, Colas; Bettens, Stijn; Blinder, David; Pesquet-Popescu, Béatrice; Cagnazzo, Marco; Dufaux, Frédéric; Schelkens, Peter

2016-09-01

signal processing methods from software-driven computer engineering and applied mathematics. The compressed sensing theory in particular established a practical framework for reconstructing the scene content using few linear combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the scene as well. This overview paper discusses contributions in the field of compressed digital holography at the micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale where much higher resolution holograms must be acquired and processed on the computer.

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

PubMed Central

Ibitoye, Morufu Olusola; Hamzaid, Nur Azah; Zuniga, Jorge M.; Hasnan, Nazirah; Wahab, Ahmad Khairi Abdul

2014-01-01

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity. PMID:25479326

Signal processing for molecular and cellular biological physics: an emerging field.

PubMed

Little, Max A; Jones, Nick S

2013-02-13

Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Signal processing for molecular and cellular biological physics: an emerging field

PubMed Central

Little, Max A.; Jones, Nick S.

2013-01-01

Recent advances in our ability to watch the molecular and cellular processes of life in action—such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer—raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied. PMID:23277603

Digital Radar-Signal Processors Implemented in FPGAs

NASA Technical Reports Server (NTRS)

Berkun, Andrew; Andraka, Ray

2004-01-01

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

An Informative Interpretation of Decision Theory: The Information Theoretic Basis for Signal-to-Noise Ratio and Log Likelihood Ratio

DOE PAGES

Polcari, J.

2013-08-16

The signal processing concept of signal-to-noise ratio (SNR), in its role as a performance measure, is recast within the more general context of information theory, leading to a series of useful insights. Establishing generalized SNR (GSNR) as a rigorous information theoretic measure inherent in any set of observations significantly strengthens its quantitative performance pedigree while simultaneously providing a specific definition under general conditions. This directly leads to consideration of the log likelihood ratio (LLR): first, as the simplest possible information-preserving transformation (i.e., signal processing algorithm) and subsequently, as an absolute, comparable measure of information for any specific observation exemplar. Furthermore,more » the information accounting methodology that results permits practical use of both GSNR and LLR as diagnostic scalar performance measurements, directly comparable across alternative system/algorithm designs, applicable at any tap point within any processing string, in a form that is also comparable with the inherent performance bounds due to information conservation.« less

Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements

NASA Astrophysics Data System (ADS)

Stewart, Kyle B.

Multiple-input multiple-output (MIMO) radar is an emerging set of technologies designed to extend the capabilities of multi-channel radar systems. While conventional radar architectures emphasize the use of antenna array beamforming to maximize real-time power on target, MIMO radar systems instead attempt to preserve some degree of independence between their received signals and to exploit this expanded matrix of target measurements in the signal-processing domain. Specifically the use of sparse “virtual” antenna arrays may allow MIMO radars to achieve gains over traditional multi-channel systems by post-processing diverse received signals to implement both transmit and receive beamforming at all points of interest within a given scene. MIMO architectures have been widely examined for use in radar target detection, but these systems may yet be ideally suited to real and synthetic aperture radar imaging applications where their proposed benefits include improved resolutions, expanded area coverage, novel modes of operation, and a reduction in hardware size, weight, and cost. While MIMO radar's theoretical benefits have been well established in the literature, its practical limitations have not received great attention thus far. The effective use of MIMO radar techniques requires a diversity of signals, and to date almost all MIMO system demonstrations have made use of time-staggered transmission to satisfy this requirement. Doing so is reliable but can be prohibitively slow. Waveform-diverse systems have been proposed as an alternative in which multiple, independent waveforms are broadcast simultaneously over a common bandwidth and separated on receive using signal processing. Operating in this way is much faster than its time-diverse equivalent, but finding a set of suitable waveforms for this technique has proven to be a difficult problem. In light of this, many have questioned the practicality of MIMO radar imaging and whether or not its theoretical benefits may be extended to real systems. Work in this writing focuses specifically on the practical aspects of MIMO radar imaging systems and provides performance data sourced from experimental measurements made using a four-channel software-defined MIMO radar platform. Demonstrations of waveform-diverse imaging data products are provided and compared directly against time-diverse equivalents in order to assess the performance of prospective MIMO waveforms. These are sourced from the pseudo-noise, short-term shift orthogonal, and orthogonal frequency multiplexing signal families while experimental results demonstrate waveform-diverse measurements of polarimetric radar cross section, top-down stationary target images, and finally volumetric MIMO synthetic aperture radar imagery. The data presented represents some of the first available concerning the overall practicality of waveform-diverse MIMO radar architectures, and results suggest that such configurations may achieve a reasonable degree of performance even in the presence of significant practical limitations.

Working Memory and Hearing Aid Processing: Literature Findings, Future Directions, and Clinical Applications

PubMed Central

Souza, Pamela; Arehart, Kathryn; Neher, Tobias

2015-01-01

Working memory—the ability to process and store information—has been identified as an important aspect of speech perception in difficult listening environments. Working memory can be envisioned as a limited-capacity system which is engaged when an input signal cannot be readily matched to a stored representation or template. This “mismatch” is expected to occur more frequently when the signal is degraded. Because working memory capacity varies among individuals, those with smaller capacity are expected to demonstrate poorer speech understanding when speech is degraded, such as in background noise. However, it is less clear whether (and how) working memory should influence practical decisions, such as hearing treatment. Here, we consider the relationship between working memory capacity and response to specific hearing aid processing strategies. Three types of signal processing are considered, each of which will alter the acoustic signal: fast-acting wide-dynamic range compression, which smooths the amplitude envelope of the input signal; digital noise reduction, which may inadvertently remove speech signal components as it suppresses noise; and frequency compression, which alters the relationship between spectral peaks. For fast-acting wide-dynamic range compression, a growing body of data suggests that individuals with smaller working memory capacity may be more susceptible to such signal alterations, and may receive greater amplification benefit with “low alteration” processing. While the evidence for a relationship between wide-dynamic range compression and working memory appears robust, the effects of working memory on perceptual response to other forms of hearing aid signal processing are less clear cut. We conclude our review with a discussion of the opportunities (and challenges) in translating information on individual working memory into clinical treatment, including clinically feasible measures of working memory. PMID:26733899

Practical Designs of Brain-Computer Interfaces Based on the Modulation of EEG Rhythms

NASA Astrophysics Data System (ADS)

Wang, Yijun; Gao, Xiaorong; Hong, Bo; Gao, Shangkai

A brain-computer interface (BCI) is a communication channel which does not depend on the brain's normal output pathways of peripheral nerves and muscles [1-3]. It supplies paralyzed patients with a new approach to communicate with the environment. Among various brain monitoring methods employed in current BCI research, electroencephalogram (EEG) is the main interest due to its advantages of low cost, convenient operation and non-invasiveness. In present-day EEG-based BCIs, the following signals have been paid much attention: visual evoked potential (VEP), sensorimotor mu/beta rhythms, P300 evoked potential, slow cortical potential (SCP), and movement-related cortical potential (MRCP). Details about these signals can be found in chapter "Brain Signals for Brain-Computer Interfaces". These systems offer some practical solutions (e.g., cursor movement and word processing) for patients with motor disabilities.

An integrated domain specific language for post-processing and visualizing electrophysiological signals in Java.

PubMed

Strasser, T; Peters, T; Jagle, H; Zrenner, E; Wilke, R

2010-01-01

Electrophysiology of vision - especially the electroretinogram (ERG) - is used as a non-invasive way for functional testing of the visual system. The ERG is a combined electrical response generated by neural and non-neuronal cells in the retina in response to light stimulation. This response can be recorded and used for diagnosis of numerous disorders. For both clinical practice and clinical trials it is important to process those signals in an accurate and fast way and to provide the results as structured, consistent reports. Therefore, we developed a freely available and open-source framework in Java (http://www.eye.uni-tuebingen.de/project/idsI4sigproc). The framework is focused on an easy integration with existing applications. By leveraging well-established software patterns like pipes-and-filters and fluent interfaces as well as by designing the application programming interfaces (API) as an integrated domain specific language (DSL) the overall framework provides a smooth learning curve. Additionally, it already contains several processing methods and visualization features and can be extended easily by implementing the provided interfaces. In this way, not only can new processing methods be added but the framework can also be adopted for other areas of signal processing. This article describes in detail the structure and implementation of the framework and demonstrate its application through the software package used in clinical practice and clinical trials at the University Eye Hospital Tuebingen one of the largest departments in the field of visual electrophysiology in Europe.

Photonic Materials and Devices for RF (mmW) Sensing and Imaging

DTIC Science & Technology

2012-12-31

wave encoding thereby eliminating the need for bulky LO distribution cables. Also, optical processing techniques can be utilized to provide simple... optical powers, can be close to unity and low -noise photodetectors make the detection of exceedingly low power millimeter-waves practical. In... optically -filtering the modulated signal to pass only a single sideband and detecting the resultant optical signal with a low -noise photodetector we have

Remote Entanglement by Coherent Multiplication of Concurrent Quantum Signals

NASA Astrophysics Data System (ADS)

Roy, Ananda; Jiang, Liang; Stone, A. Douglas; Devoret, Michel

2015-10-01

Concurrent remote entanglement of distant, noninteracting quantum entities is a crucial function for quantum information processing. In contrast with the existing protocols which employ the addition of signals to generate entanglement between two remote qubits, the continuous variable protocol we present is based on the multiplication of signals. This protocol can be straightforwardly implemented by a novel Josephson junction mixing circuit. Our scheme would be able to generate provable entanglement even in the presence of practical imperfections: finite quantum efficiency of detectors and undesired photon loss in current state-of-the-art devices.

Towards a practical Johnson noise thermometer for long-term measurements in harsh environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenen, Adam; Pearce, Jonathan; Cruickshank, David

The impact of mechanical and chemical changes in conventional sensors such as thermocouples and resistance thermometers can be avoided by instead using temperature sensors based on fundamental thermometry. A prime example of this is Johnson noise thermometry, which is based on measurement of the fluctuations in the voltage of a resistor arising from thermal motion of charge carriers - i.e. the 'Johnson noise'. A Johnson noise thermometer never needs calibration and is insensitive to the condition of the sensor material. It is therefore ideally suited to long-term temperature measurements in harsh environments, such as nuclear reactor coolant circuits, in-pile measurements,more » nuclear waste management and storage, and severe accident monitoring. There have been a number of previous attempts to develop a Johnson noise thermometer for the nuclear industry, but none have reached commercial exploitation because of technical problems in practical implementation. The main challenge is to extract the tiny Johnson noise signal from ambient electrical noise influences, both from the internal amplification electronics, and from external electrical noise sources. Recent advances in electronics technology and digital signal processing techniques have opened up new possibilities for developing a viable, practical Johnson noise thermometer. We describe a project funded by the UK Technology Strategy Board (now Innovate UK) 'Developing the nuclear supply chain' call, currently underway, to develop a practical Johnson noise thermometer that makes use of innovative electronics for ultralow noise amplification and signal processing. The new electronics technology has the potential to help overcome the problems encountered with previous attempts at constructing a practical Johnson noise thermometer. An outline of the new developments is presented, together with an overview of the current status of the project. (authors)« less

Comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Sullivan, Malcolm N.; Chan, Kam Wai Clifford; Boyd, Robert W.

2010-11-15

We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantummore » ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.« less

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

NASA Astrophysics Data System (ADS)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

47 CFR 76.1908 - Certain practices not prohibited.

Code of Federal Regulations, 2014 CFR

2014-10-01

... for the transport, processing and display of audiovisual signals or data, such as between analog and digital formats and between PAL and NTSC or RGB and Y,Pb,Pr. [68 FR 66735, Nov. 28, 2003, as amended at 76...

47 CFR 76.1908 - Certain practices not prohibited.

Code of Federal Regulations, 2011 CFR

2011-10-01

... for the transport, processing and display of audiovisual signals or data, such as between analog and digital formats and between PAL and NTSC or RGB and Y,Pb,Pr. [68 FR 66735, Nov. 28, 2003, as amended at 76...

47 CFR 76.1908 - Certain practices not prohibited.

Code of Federal Regulations, 2012 CFR

2012-10-01

... for the transport, processing and display of audiovisual signals or data, such as between analog and digital formats and between PAL and NTSC or RGB and Y,Pb,Pr. [68 FR 66735, Nov. 28, 2003, as amended at 76...

47 CFR 76.1908 - Certain practices not prohibited.

Code of Federal Regulations, 2013 CFR

2013-10-01

... for the transport, processing and display of audiovisual signals or data, such as between analog and digital formats and between PAL and NTSC or RGB and Y,Pb,Pr. [68 FR 66735, Nov. 28, 2003, as amended at 76...

Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

NASA Astrophysics Data System (ADS)

Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

2007-12-01

We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

Encoder fault analysis system based on Moire fringe error signal

NASA Astrophysics Data System (ADS)

Gao, Xu; Chen, Wei; Wan, Qiu-hua; Lu, Xin-ran; Xie, Chun-yu

2018-02-01

Aiming at the problem of any fault and wrong code in the practical application of photoelectric shaft encoder, a fast and accurate encoder fault analysis system is researched from the aspect of Moire fringe photoelectric signal processing. DSP28335 is selected as the core processor and high speed serial A/D converter acquisition card is used. And temperature measuring circuit using AD7420 is designed. Discrete data of Moire fringe error signal is collected at different temperatures and it is sent to the host computer through wireless transmission. The error signal quality index and fault type is displayed on the host computer based on the error signal identification method. The error signal quality can be used to diagnosis the state of error code through the human-machine interface.

Practical photon number detection with electric field-modulated silicon avalanche photodiodes.

PubMed

Thomas, O; Yuan, Z L; Shields, A J

2012-01-24

Low-noise single-photon detection is a prerequisite for quantum information processing using photonic qubits. In particular, detectors that are able to accurately resolve the number of photons in an incident light pulse will find application in functions such as quantum teleportation and linear optics quantum computing. More generally, such a detector will allow the advantages of quantum light detection to be extended to stronger optical signals, permitting optical measurements limited only by fluctuations in the photon number of the source. Here we demonstrate a practical high-speed device, which allows the signals arising from multiple photon-induced avalanches to be precisely discriminated. We use a type of silicon avalanche photodiode in which the lateral electric field profile is strongly modulated in order to realize a spatially multiplexed detector. Clearly discerned multiphoton signals are obtained by applying sub-nanosecond voltage gates in order to restrict the detector current.

Exploring the physical layer frontiers of cellular uplink: The Vienna LTE-A Uplink Simulator.

PubMed

Zöchmann, Erich; Schwarz, Stefan; Pratschner, Stefan; Nagel, Lukas; Lerch, Martin; Rupp, Markus

Communication systems in practice are subject to many technical/technological constraints and restrictions. Multiple input, multiple output (MIMO) processing in current wireless communications, as an example, mostly employs codebook-based pre-coding to save computational complexity at the transmitters and receivers. In such cases, closed form expressions for capacity or bit-error probability are often unattainable; effects of realistic signal processing algorithms on the performance of practical communication systems rather have to be studied in simulation environments. The Vienna LTE-A Uplink Simulator is a 3GPP LTE-A standard compliant MATLAB-based link level simulator that is publicly available under an academic use license, facilitating reproducible evaluations of signal processing algorithms and transceiver designs in wireless communications. This paper reviews research results that have been obtained by means of the Vienna LTE-A Uplink Simulator, highlights the effects of single-carrier frequency-division multiplexing (as the distinguishing feature to LTE-A downlink), extends known link adaptation concepts to uplink transmission, shows the implications of the uplink pilot pattern for gathering channel state information at the receiver and completes with possible future research directions.

Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.

PubMed

Stec, Bronisław; Susek, Waldemar

2018-05-06

Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.

The Ensemble Kalman filter: a signal processing perspective

NASA Astrophysics Data System (ADS)

Roth, Michael; Hendeby, Gustaf; Fritsche, Carsten; Gustafsson, Fredrik

2017-12-01

The ensemble Kalman filter (EnKF) is a Monte Carlo-based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear, and non-Gaussian state estimation problems. Its ability to handle state dimensions in the order of millions has made the EnKF a popular algorithm in different geoscientific disciplines. Despite a similarly vital need for scalable algorithms in signal processing, e.g., to make sense of the ever increasing amount of sensor data, the EnKF is hardly discussed in our field. This self-contained review is aimed at signal processing researchers and provides all the knowledge to get started with the EnKF. The algorithm is derived in a KF framework, without the often encountered geoscientific terminology. Algorithmic challenges and required extensions of the EnKF are provided, as well as relations to sigma point KF and particle filters. The relevant EnKF literature is summarized in an extensive survey and unique simulation examples, including popular benchmark problems, complement the theory with practical insights. The signal processing perspective highlights new directions of research and facilitates the exchange of potentially beneficial ideas, both for the EnKF and high-dimensional nonlinear and non-Gaussian filtering in general.

Advanced Signal Processing for High Temperatures Health Monitoring of Condensed Water Height in Steam Pipes

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Bar-Cohen, Yoseph; Lee, Hyeong Jae; Takano, Nobuyuki; Bao, Xiaoqi

2013-01-01

An advanced signal processing methodology is being developed to monitor the height of condensed water thru the wall of a steel pipe while operating at temperatures as high as 250deg. Using existing techniques, previous study indicated that, when the water height is low or there is disturbance in the environment, the predicted water height may not be accurate. In recent years, the use of the autocorrelation and envelope techniques in the signal processing has been demonstrated to be a very useful tool for practical applications. In this paper, various signal processing techniques including the auto correlation, Hilbert transform, and the Shannon Energy Envelope methods were studied and implemented to determine the water height in the steam pipe. The results have shown that the developed method provides a good capability for monitoring the height in the regular conditions. An alternative solution for shallow water or no water conditions based on a developed hybrid method based on Hilbert transform (HT) with a high pass filter and using the optimized windowing technique is suggested. Further development of the reported methods would provide a powerful tool for the identification of the disturbances of water height inside the pipe.

Digital approach to stabilizing optical frequency combs and beat notes of CW lasers

NASA Astrophysics Data System (ADS)

Čížek, Martin; Číp, Ondřej; Å míd, Radek; Hrabina, Jan; Mikel, Břetislav; Lazar, Josef

2013-10-01

In cases when it is necessary to lock optical frequencies generated by an optical frequency comb to a precise radio frequency (RF) standard (GPS-disciplined oscillator, H-maser, etc.) the usual practice is to implement phase and frequency-locked loops. Such system takes the signal generated by the RF standard (usually 10 MHz or 100 MHz) as a reference and stabilizes the repetition and offset frequencies of the comb contained in the RF output of the f-2f interferometer. These control loops are usually built around analog electronic circuits processing the output signals from photo detectors. This results in transferring the stability of the standard from RF to optical frequency domain. The presented work describes a different approach based on digital signal processing and software-defined radio algorithms used for processing the f-2f and beat-note signals. Several applications of digital phase and frequency locks to a RF standard are demonstrated: the repetition (frep) and offset frequency (fceo) of the comb, and the frequency of the beat note between a CW laser source and a single component of the optical frequency comb spectrum.

Model-Based Fault Diagnosis for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Green, Michael D.; Duyar, Ahmet; Litt, Jonathan S.

1998-01-01

Tests are described which, when used to augment the existing periodic maintenance and pre-flight checks of T700 engines, can greatly improve the chances of uncovering a problem compared to the current practice. These test signals can be used to expose and differentiate between faults in various components by comparing the responses of particular engine variables to the expected. The responses can be processed on-line in a variety of ways which have been shown to reveal and identify faults. The combination of specific test signals and on-line processing methods provides an ad hoc approach to the isolation of faults which might not otherwise be detected during pre-flight checkout.

Range Measurement as Practiced in the Deep Space Network

NASA Technical Reports Server (NTRS)

Berner, Jeff B.; Bryant, Scott H.; Kinman, Peter W.

2007-01-01

Range measurements are used to improve the trajectory models of spacecraft tracked by the Deep Space Network. The unique challenge of deep-space ranging is that the two-way delay is long, typically many minutes, and the signal-to-noise ratio is small. Accurate measurements are made under these circumstances by means of long correlations that incorporate Doppler rate-aiding. This processing is done with commercial digital signal processors, providing a flexibility in signal design that can accommodate both the traditional sequential ranging signal and pseudonoise range codes. Accurate range determination requires the calibration of the delay within the tracking station. Measurements with a standard deviation of 1 m have been made.

Retrieval-practice task affects relationship between working memory capacity and retrieval-induced forgetting.

PubMed

Storm, Benjamin C; Bui, Dung C

2016-11-01

Retrieving a subset of items from memory can cause forgetting of other items in memory, a phenomenon referred to as retrieval-induced forgetting (RIF). Individuals who exhibit greater amounts of RIF have been shown to also exhibit superior working memory capacity (WMC) and faster stop-signal reaction times (SSRTs), results which have been interpreted as suggesting that RIF reflects an inhibitory process that is mediated by the processes of executive control. Across four experiments, we sought to further elucidate this issue by manipulating the way in which participants retrieved items during retrieval practice and examining how the resulting effects of forgetting correlated with WMC (Experiments 1-3) and SSRT (Experiment 4). Significant correlations were observed when participants retrieved items from an earlier study phase (within-list retrieval practice), but not when participants generated items from semantic memory (extra-list retrieval practice). These results provide important new insight into the role of executive-control processes in RIF.

Systems for low frequency seismic and infrasound detection of geo-pressure transition zones

DOEpatents

Shook, G. Michael; LeRoy, Samuel D.; Benzing, William M.

2007-10-16

Methods for determining the existence and characteristics of a gradational pressurized zone within a subterranean formation are disclosed. One embodiment involves employing an attenuation relationship between a seismic response signal and increasing wavelet wavelength, which relationship may be used to detect a gradational pressurized zone and/or determine characteristics thereof. In another embodiment, a method for analyzing data contained within a response signal for signal characteristics that may change in relation to the distance between an input signal source and the gradational pressurized zone is disclosed. In a further embodiment, the relationship between response signal wavelet frequency and comparative amplitude may be used to estimate an optimal wavelet wavelength or range of wavelengths used for data processing or input signal selection. Systems for seismic exploration and data analysis for practicing the above-mentioned method embodiments are also disclosed.

Implementation of a Portable Personal EKG Signal Monitoring System

NASA Astrophysics Data System (ADS)

Tan, Tan-Hsu; Chang, Ching-Su; Chen, Yung-Fu; Lee, Cheng

This research develops a portable personal EKG signal monitoring system to help patients monitor their EKG signals instantly to avoid the occurrence of tragedies. This system is built with two main units: signal pro-cessing unit and monitoring and evaluation unit. The first unit consists of EKG signal sensor, signal amplifier, digitalization circuit, and related control circuits. The second unit is a software tool developed on an embedded Linux platform (called CSA). Experimental result indicates that the proposed system has the practical potential for users in health monitoring. It is demonstrated to be more convenient and with greater portability than the conventional PC-based EKG signal monitoring systems. Furthermore, all the application units embedded in the system are built with open source codes, no licensed fee is required for operating systems and authorized applications. Thus, the building cost is much lower than the traditional systems.

Quantification of MDL-induced signal degradation in MIMO-OFDM mode-division multiplexing systems.

PubMed

Tian, Yu; Li, Juhao; Zhu, Paikun; Wu, Zhongying; Chen, Yuanxiang; He, Yongqi; Chen, Zhangyuan

2016-08-22

Mode-division multiplexing (MDM) transmission over few-mode optical fiber has emerged as a promising technology to enhance transmission capacity, in which multiple-input-multiple-output (MIMO) digital signal processing (DSP) after coherent detection is used to demultiplex the signals. Compared with conventional single-mode systems, MIMO-MDM systems suffer non-recoverable signal degradation induced by mode-dependent loss (MDL). In this paper, the MDL-induced signal degradation in orthogonal-frequency-division-multiplexing (OFDM) MDM systems is theoretically quantified in terms of mode-average error vector magnitude (EVM) through frequency domain norm analysis. A novel scalar MDL metric is proposed considering the probability distribution of the practical MDM input signals, and a closed-form expression for EVM measured after zero-force (ZF) MIMO equalization is derived. Simulation results show that the EVM estimations utilizing the novel MDL metric remain unbiased for unrepeated links. For a 6 × 100 km 20-mode MDM transmission system, the estimation accuracy is improved by more than 90% compared with that utilizing traditional condition number (CN) based MDL metric. The proposed MDL metric can be used to predict the MDL-induced SNR penalty in a theoretical manner, which will be beneficial for the design of practical MIMO-MDM systems.

Clustering for unsupervised fault diagnosis in nuclear turbine shut-down transients

NASA Astrophysics Data System (ADS)

Baraldi, Piero; Di Maio, Francesco; Rigamonti, Marco; Zio, Enrico; Seraoui, Redouane

2015-06-01

Empirical methods for fault diagnosis usually entail a process of supervised training based on a set of examples of signal evolutions "labeled" with the corresponding, known classes of fault. However, in practice, the signals collected during plant operation may be, very often, "unlabeled", i.e., the information on the corresponding type of occurred fault is not available. To cope with this practical situation, in this paper we develop a methodology for the identification of transient signals showing similar characteristics, under the conjecture that operational/faulty transient conditions of the same type lead to similar behavior in the measured signals evolution. The methodology is founded on a feature extraction procedure, which feeds a spectral clustering technique, embedding the unsupervised fuzzy C-means (FCM) algorithm, which evaluates the functional similarity among the different operational/faulty transients. A procedure for validating the plausibility of the obtained clusters is also propounded based on physical considerations. The methodology is applied to a real industrial case, on the basis of 148 shut-down transients of a Nuclear Power Plant (NPP) steam turbine.

Software-defined microwave photonic filter with high reconfigurable resolution

PubMed Central

Wei, Wei; Yi, Lilin; Jaouën, Yves; Hu, Weisheng

2016-01-01

Microwave photonic filters (MPFs) are of great interest in radio frequency systems since they provide prominent flexibility on microwave signal processing. Although filter reconfigurability and tunability have been demonstrated repeatedly, it is still difficult to control the filter shape with very high precision. Thus the MPF application is basically limited to signal selection. Here we present a polarization-insensitive single-passband arbitrary-shaped MPF with ~GHz bandwidth based on stimulated Brillouin scattering (SBS) in optical fibre. For the first time the filter shape, bandwidth and central frequency can all be precisely defined by software with ~MHz resolution. The unprecedented multi-dimensional filter flexibility offers new possibilities to process microwave signals directly in optical domain with high precision thus enhancing the MPF functionality. Nanosecond pulse shaping by implementing precisely defined filters is demonstrated to prove the filter superiority and practicability. PMID:27759062

Software-defined microwave photonic filter with high reconfigurable resolution.

PubMed

Wei, Wei; Yi, Lilin; Jaouën, Yves; Hu, Weisheng

2016-10-19

Microwave photonic filters (MPFs) are of great interest in radio frequency systems since they provide prominent flexibility on microwave signal processing. Although filter reconfigurability and tunability have been demonstrated repeatedly, it is still difficult to control the filter shape with very high precision. Thus the MPF application is basically limited to signal selection. Here we present a polarization-insensitive single-passband arbitrary-shaped MPF with ~GHz bandwidth based on stimulated Brillouin scattering (SBS) in optical fibre. For the first time the filter shape, bandwidth and central frequency can all be precisely defined by software with ~MHz resolution. The unprecedented multi-dimensional filter flexibility offers new possibilities to process microwave signals directly in optical domain with high precision thus enhancing the MPF functionality. Nanosecond pulse shaping by implementing precisely defined filters is demonstrated to prove the filter superiority and practicability.

Laser anemometry for hot flows

NASA Astrophysics Data System (ADS)

Kugler, P.; Langer, G.

1987-07-01

The fundamental principles, instrumentation, and practical operation of LDA and laser-transit-anemometry systems for measuring velocity profiles and the degree of turbulence in high-temperature flows are reviewed and illustrated with diagrams, drawings and graphs of typical data. Consideration is given to counter, tracker, spectrum-analyzer and correlation methods of LDA signal processing; multichannel analyzer and cross correlation methods for LTA data; LTA results for a small liquid fuel rocket motor; and experiments demonstrating the feasibility of an optoacoustic demodulation scheme for LDA signals from unsteady flows.

Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

PubMed

Russo, Michael B; Stetz, Melba C; Thomas, Maria L

2005-07-01

Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue.

Guided wave imaging of oblique reflecting interfaces in pipes using common-source synthetic focusing

NASA Astrophysics Data System (ADS)

Sun, Zeqing; Sun, Anyu; Ju, Bing-Feng

2018-04-01

Cross-mode-family mode conversion and secondary reflection of guided waves in pipes complicate the processing of guided waves signals, and can cause false detection. In this paper, filters operating in the spectral domain of wavenumber, circumferential order and frequency are designed to suppress the signal components of unwanted mode-family and unwanted traveling direction. Common-source synthetic focusing is used to reconstruct defect images from the guided wave signals. Simulations of the reflections from linear oblique defects and a semicircle defect are separately implemented. Defect images, which are reconstructed from the simulation results under different excitation conditions, are comparatively studied in terms of axial resolution, reflection amplitude, detectable oblique angle and so on. Further, the proposed method is experimentally validated by detecting linear cracks with various oblique angles (10-40°). The proposed method relies on the guided wave signals that are captured during 2-D scanning of a cylindrical area on the pipe. The redundancy of the signals is analyzed to reduce the time-consumption of the scanning process and to enhance the practicability of the proposed method.

Travelling-wave resonant four-wave mixing breaks the limits of cavity-enhanced all-optical wavelength conversion.

PubMed

Morichetti, Francesco; Canciamilla, Antonio; Ferrari, Carlo; Samarelli, Antonio; Sorel, Marc; Melloni, Andrea

2011-01-01

Wave mixing inside optical resonators, while experiencing a large enhancement of the nonlinear interaction efficiency, suffers from strong bandwidth constraints, preventing its practical exploitation for processing broad-band signals. Here we show that such limits are overcome by the new concept of travelling-wave resonant four-wave mixing (FWM). This approach combines the efficiency enhancement provided by resonant propagation with a wide-band conversion process. Compared with conventional FWM in bare waveguides, it exhibits higher robustness against chromatic dispersion and propagation loss, while preserving transparency to modulation formats. Travelling-wave resonant FWM has been demonstrated in silicon-coupled ring resonators and was exploited to realize a 630-μm-long wavelength converter operating over a wavelength range wider than 60 nm and with 28-dB gain with respect to a bare waveguide of the same physical length. Full compatibility of the travelling-wave resonant FWM with optical signal processing applications has been demonstrated through signal retiming and reshaping at 10 Gb s(-1).

Travelling-wave resonant four-wave mixing breaks the limits of cavity-enhanced all-optical wavelength conversion

PubMed Central

Morichetti, Francesco; Canciamilla, Antonio; Ferrari, Carlo; Samarelli, Antonio; Sorel, Marc; Melloni, Andrea

2011-01-01

Wave mixing inside optical resonators, while experiencing a large enhancement of the nonlinear interaction efficiency, suffers from strong bandwidth constraints, preventing its practical exploitation for processing broad-band signals. Here we show that such limits are overcome by the new concept of travelling-wave resonant four-wave mixing (FWM). This approach combines the efficiency enhancement provided by resonant propagation with a wide-band conversion process. Compared with conventional FWM in bare waveguides, it exhibits higher robustness against chromatic dispersion and propagation loss, while preserving transparency to modulation formats. Travelling-wave resonant FWM has been demonstrated in silicon-coupled ring resonators and was exploited to realize a 630-μm-long wavelength converter operating over a wavelength range wider than 60 nm and with 28-dB gain with respect to a bare waveguide of the same physical length. Full compatibility of the travelling-wave resonant FWM with optical signal processing applications has been demonstrated through signal retiming and reshaping at 10 Gb s−1 PMID:21540838

Instructional Specifications for Sentence Combining.

ERIC Educational Resources Information Center

Lawlor, Joseph

With particular focus on the need to provide a practical, systematic introduction to the concept of sentence combining and to the signals used to control the various combining operations, this paper provides detailed specifications for including sentence combining as part of a comprehensive plan for teaching the composing process. The…

Electrophysiology for biomedical engineering students: a practical and theoretical course in animal electrocorticography.

PubMed

Albarracín, Ana L; Farfán, Fernando D; Coletti, Marcos A; Teruya, Pablo Y; Felice, Carmelo J

2016-09-01

The major challenge in laboratory teaching is the application of abstract concepts in simple and direct practical lessons. However, students rarely have the opportunity to participate in a laboratory that combines practical learning with a realistic research experience. In the Biomedical Engineering career, we offer short and optional courses to complement studies for students as they initiate their Graduation Project. The objective of these theoretical and practical courses is to introduce students to the topics of their projects. The present work describes an experience in electrophysiology to teach undergraduate students how to extract cortical information using electrocorticographic techniques. Students actively participate in some parts of the experience and then process and analyze the data obtained with different signal processing tools. In postlaboratory evaluations, students described the course as an exceptional opportunity for students interested in following a postgraduate science program and fully appreciated their contents. Copyright © 2016 The American Physiological Society.

Detecting the spatial chirp signals by fractional Fourier lens with transformation materials

NASA Astrophysics Data System (ADS)

Chen, J.; Hu, J.

2018-02-01

Fractional Fourier transform (FrFT) is the general form of the Fourier transform and is an important tool in signal processing. As one typical application of FrFT, detecting the chirp rate (CR, or known as the rate of frequency change) of a chirp signal is important in many optical measurements. The optical FrFT that based on graded index lens fails to detect the high CR chirp because the short wave propagation distance of the impulse in the lens will weaken the paraxial approximation condition. With the help of transformation optics, the improved FrFT lens is proposed to adjust the high CR as well as the impulse location of the given input chirp signal. The designed transformation materials can implement the effect of space compression, making the input chirp signal is equivalent to have lower CR, therefore the system can satisfy the paraxial approximation better. As a result, this lens can improve the detection precision for the high CR. The numerical simulations verified the design. The proposed device may have both theoretical and practical values, and the design demonstrates the ability and flexibility of TO in spatial signal processing.

Compressive sensing scalp EEG signals: implementations and practical performance.

PubMed

Abdulghani, Amir M; Casson, Alexander J; Rodriguez-Villegas, Esther

2012-11-01

Highly miniaturised, wearable computing and communication systems allow unobtrusive, convenient and long term monitoring of a range of physiological parameters. For long term operation from the physically smallest batteries, the average power consumption of a wearable device must be very low. It is well known that the overall power consumption of these devices can be reduced by the inclusion of low power consumption, real-time compression of the raw physiological data in the wearable device itself. Compressive sensing is a new paradigm for providing data compression: it has shown significant promise in fields such as MRI; and is potentially suitable for use in wearable computing systems as the compression process required in the wearable device has a low computational complexity. However, the practical performance very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Long term electroencephalography (EEG) is a fundamental tool for the investigation of neurological disorders and is increasingly used in many non-medical applications, such as brain-computer interfaces. This article investigates in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals.

Layover and shadow detection based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Huanxin, Zou; Bin, Cai; Changzhou, Fan; Yun, Ren

2014-03-01

Distributed spaceborne single-baseline InSAR is an effective technique to get high quality Digital Elevation Model. Layover and Shadow are ubiquitous phenomenon in SAR images because of geometric relation of SAR imaging. In the signal processing of single-baseline InSAR, the phase singularity of Layover and Shadow leads to the phase difficult to filtering and unwrapping. This paper analyzed the geometric and signal model of the Layover and Shadow fields. Based on the interferometric signal autocorrelation matrix, the paper proposed the signal number estimation method based on information theoretic criteria, to distinguish Layover and Shadow from normal InSAR fields. The effectiveness and practicability of the method proposed in the paper are validated in the simulation experiments and theoretical analysis.

A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

PubMed Central

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-01-01

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel. PMID:25264951

A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

PubMed

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-09-26

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

Sonic Simulation of Near Projectile Hits

NASA Technical Reports Server (NTRS)

Statman, J. I.; Rodemich, E. R.

1988-01-01

Measured frequencies identify projectiles and indicate miss distances. Developmental battlefield-simulation system for training soldiers uses sounds emitted by incoming projectiles to identify projectiles and indicate miss distances. Depending on projectile type and closeness of each hit, system generates "kill" or "near-kill" indication. Artillery shell simulated by lightweight plastic projectile launched by compressed air. Flow of air through groove in nose of projectile generates acoustic tone. Each participant carries audio receiver measure and process tone signal. System performs fast Fourier transforms of received tone to obtain dominant frequency during each succeeding interval of approximately 40 ms (an interval determined from practical signal-processing requirements). With modifications, system concept applicable to collision-warning or collision-avoidance systems.

Practical Considerations for Optimizing Position Sensitivity in Arrays of Position-sensitive TES's

NASA Technical Reports Server (NTRS)

Smith, Stephen J.; Bandler, Simon R.; Figueroa-Feliciano, Encetali; Iyomoto, Naoko; Kelley, Richard L.; Kilbourne, Caroline A.; Porder, Frederick S.; Sadleir, John E.

2007-01-01

We are developing Position-Sensitive Transitions-Edge Sensors (PoST's) for future X-ray astronomy missions such as NASA's Constellation-X. The PoST consists of one or more Transitions Edge Sensors (TES's) thermally connected to a large X-ray absorber, which through heat diffusion, gives rise to position dependence. The development of PoST's is motivated by the desire to achieve the largest the focal-plan coverage with the fewest number of readout channels. In order to develop a practical array, consisting of an inner pixellated core with an outer array of large absorber PoST's, we must be able to simultaneously read out all (-1800) channels in the array. This is achievable using time division multiplexing (TDM), but does set stringent slew rate requirements on the array. Typically, we must damp the pulses to reduce the slew rate of the input signal to the TDM. This is achieved by applying a low-pass analog filter with large inductance to the signal. This attenuates the high frequency components of the signal, essential for position discrimination in PoST's, relative to the white noise of the readout chain and degrades the position sensitivity. Using numerically simulated data, we investigate the position sensing ability of typical PoST designs under such high inductance conditions. We investigate signal-processing techniques for optimal determination of the event position and discuss the practical considerations for real-time implementation.

Wearable sensor glove based on conducting fabric using electrodermal activity and pulse-wave sensors for e-health application.

PubMed

Lee, Youngbum; Lee, Byungwoo; Lee, Myoungho

2010-03-01

Improvement of the quality and efficiency of health in medicine, both at home and the hospital, calls for improved sensors that might be included in a common carrier such as a wearable sensor device to measure various biosignals and provide healthcare services that use e-health technology. Designed to be user-friendly, smart clothes and gloves respond well to the end users for health monitoring. This study describes a wearable sensor glove that is equipped with an electrodermal activity (EDA) sensor, pulse-wave sensor, conducting fabric, and an embedded system. The EDA sensor utilizes the relationship between drowsiness and the EDA signal. The EDA sensors were made using a conducting fabric instead of silver chloride electrodes, as a more practical and practically wearable device. The pulse-wave sensor measurement system, which is widely applied in oriental medicinal practices, is also a strong element in e-health monitoring systems. The EDA and pulse-wave signal acquisition module was constructed by connecting the sensor to the glove via a conductive fabric. The signal acquisition module is then connected to a personal computer that displays the results of the EDA and pulse-wave signal processing analysis and gives accurate feedback to the user. This system is designed for a number of applications for the e-health services, including drowsiness detection and oriental medicine.

Implantable brain computer interface: challenges to neurotechnology translation.

PubMed

Konrad, Peter; Shanks, Todd

2010-06-01

This article reviews three concepts related to implantable brain computer interface (BCI) devices being designed for human use: neural signal extraction primarily for motor commands, signal insertion to restore sensation, and technological challenges that remain. A significant body of literature has occurred over the past four decades regarding motor cortex signal extraction for upper extremity movement or computer interface. However, little is discussed regarding postural or ambulation command signaling. Auditory prosthesis research continues to represent the majority of literature on BCI signal insertion. Significant hurdles continue in the technological translation of BCI implants. These include developing a stable neural interface, significantly increasing signal processing capabilities, and methods of data transfer throughout the human body. The past few years, however, have provided extraordinary human examples of BCI implant potential. Despite technological hurdles, proof-of-concept animal and human studies provide significant encouragement that BCI implants may well find their way into mainstream medical practice in the foreseeable future.

Methods and systems for low frequency seismic and infrasound detection of geo-pressure transition zones

DOEpatents

Shook, G. Michael; LeRoy, Samuel D.; Benzing, William M.

2006-07-18

Methods for determining the existence and characteristics of a gradational pressurized zone within a subterranean formation are disclosed. One embodiment involves employing an attenuation relationship between a seismic response signal and increasing wavelet wavelength, which relationship may be used to detect a gradational pressurized zone and/or determine characteristics thereof. In another embodiment, a method for analyzing data contained within a response signal for signal characteristics that may change in relation to the distance between an input signal source and the gradational pressurized zone is disclosed. In a further embodiment, the relationship between response signal wavelet frequency and comparative amplitude may be used to estimate an optimal wavelet wavelength or range of wavelengths used for data processing or input signal selection. Systems for seismic exploration and data analysis for practicing the above-mentioned method embodiments are also disclosed.

Piezoelectric extraction of ECG signal

NASA Astrophysics Data System (ADS)

Ahmad, Mahmoud Al

2016-11-01

The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other.

Spotlight: Sending Clear Signals on Complex Credentialing Process

ERIC Educational Resources Information Center

Guth, Douglas J.

2017-01-01

Credentialing programs in the U.S. are many and varied: Degrees, professional certifications, digital badges, and licenses to practice all serve as potential pathways to employment for would-be workers. However, those many approaches can also result in confusion for employers, colleges, and students when drilling down into how credentials…

Polarimetry With Phased Array Antennas: Theoretical Framework and Definitions

NASA Astrophysics Data System (ADS)

Warnick, Karl F.; Ivashina, Marianna V.; Wijnholds, Stefan J.; Maaskant, Rob

2012-01-01

For phased array receivers, the accuracy with which the polarization state of a received signal can be measured depends on the antenna configuration, array calibration process, and beamforming algorithms. A signal and noise model for a dual-polarized array is developed and related to standard polarimetric antenna figures of merit, and the ideal polarimetrically calibrated, maximum-sensitivity beamforming solution for a dual-polarized phased array feed is derived. A practical polarimetric beamformer solution that does not require exact knowledge of the array polarimetric response is shown to be equivalent to the optimal solution in the sense that when the practical beamformers are calibrated, the optimal solution is obtained. To provide a rough initial polarimetric calibration for the practical beamformer solution, an approximate single-source polarimetric calibration method is developed. The modeled instrumental polarization error for a dipole phased array feed with the practical beamformer solution and single-source polarimetric calibration was -10 dB or lower over the array field of view for elements with alignments perturbed by random rotations with 5 degree standard deviation.

External cues challenging the internal appetite control system-Overview and practical implications.

PubMed

Bilman, Els; van Kleef, Ellen; van Trijp, Hans

2017-09-02

Inadequate regulation of food intake plays an important role in the development of overweight and obesity, and is under the influence of both the internal appetite control system and external environmental cues. Especially in environments where food is overly available, external cues seem to override and/or undermine internal signals, which put severe challenges on the accurate regulation of food intake. By structuring these external cues around five different phases in the food consumption process this paper aims to provide an overview of the wide range of external cues that potentially facilitate or hamper internal signals and with that influence food intake. For each of the five phases of the food consumption process, meal initiation, meal planning, consumption phase, end of eating episode and time till next meal, the most relevant internal signals are discussed and it is explained how specific external cues exert their influence.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

PubMed

Ardila-Rey, Jorge Alfredo; Montaña, Johny; de Castro, Bruno Albuquerque; Schurch, Roger; Covolan Ulson, José Alfredo; Muhammad-Sukki, Firdaus; Bani, Nurul Aini

2018-03-29

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Laser Calibration of an Impact Disdrometer

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip T.; Jones, W. Linwood

2014-01-01

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

Methods to Manipulate and Monitor Wnt Signaling in Human Pluripotent Stem Cells.

PubMed

Huggins, Ian J; Brafman, David; Willert, Karl

2016-01-01

Human pluripotent stem cells (hPSCs) may revolutionize medical practice by providing: (a) a renewable source of cells for tissue replacement therapies, (b) a powerful system to model human diseases in a dish, and (c) a platform for examining efficacy and safety of novel drugs. Furthermore, these cells offer a unique opportunity to study early human development in vitro, in particular, the process by which a seemingly uniform cell population interacts to give rise to the three main embryonic lineages: ectoderm, endoderm. and mesoderm. This process of lineage allocation is regulated by a number of inductive signals that are mediated by growth factors, including FGF, TGFβ, and Wnt. In this book chapter, we introduce a set of tools, methods, and protocols to specifically manipulate the Wnt signaling pathway with the intention of altering the cell fate outcome of hPSCs.

Aligning a Receiving Antenna Array to Reduce Interference

NASA Technical Reports Server (NTRS)

Jongeling, Andre P.; Rogstad, David H.

2009-01-01

A digital signal-processing algorithm has been devised as a means of aligning (as defined below) the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a desired weak signal transmitted by a single distant source in the presence of an interfering signal that (1) originates at another source lying within the antenna beam and (2) occupies a frequency band significantly wider than that of the desired signal. In the original intended application of the algorithm, the desired weak signal is a spacecraft telemetry signal, the antennas are spacecraft-tracking antennas in NASA s Deep Space Network, and the source of the wide-band interfering signal is typically a radio galaxy or a planet that lies along or near the line of sight to the spacecraft. The algorithm could also afford the ability to discriminate between desired narrow-band and nearby undesired wide-band sources in related applications that include satellite and terrestrial radio communications and radio astronomy. The development of the present algorithm involved modification of a prior algorithm called SUMPLE and a predecessor called SIMPLE. SUMPLE was described in Algorithm for Aligning an Array of Receiving Radio Antennas (NPO-40574), NASA Tech Briefs Vol. 30, No. 4 (April 2006), page 54. To recapitulate: As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. Prior to the development of SUMPLE, it was common practice to effect alignment by means of a process that involves correlation of signals in pairs. SIMPLE is an example of an algorithm that effects such a process. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals.

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

SNR Degradation in Undersampled Phase Measurement Systems

PubMed Central

Salido-Monzú, David; Meca-Meca, Francisco J.; Martín-Gorostiza, Ernesto; Lázaro-Galilea, José L.

2016-01-01

A wide range of measuring applications rely on phase estimation on sinusoidal signals. These systems, where the estimation is mainly implemented in the digital domain, can generally benefit from the use of undersampling to reduce the digitizer and subsequent digital processing requirements. This may be crucial when the application characteristics necessarily imply a simple and inexpensive sensor. However, practical limitations related to the phase stability of the band-pass filter prior digitization establish restrictions to the reduction of noise bandwidth. Due to this, the undersampling intensity is practically defined by noise aliasing, taking into account the amount of signal-to-noise ratio (SNR) reduction caused by it considering the application accuracy requirements. This work analyzes the relationship between undersampling frequency and SNR reduction, conditioned by the stability requirements of the filter that defines the noise bandwidth before digitization. The effect of undersampling is quantified in a practical situation where phase differences are measured by in-phase and quadrature (I/Q) demodulation for an infrared ranging application. PMID:27783033

Should I Stop or Should I Go? The Role of Associations and Expectancies

PubMed Central

2015-01-01

Following exposure to consistent stimulus–stop mappings, response inhibition can become automatized with practice. What is learned is less clear, even though this has important theoretical and practical implications. A recent analysis indicates that stimuli can become associated with a stop signal or with a stop goal. Furthermore, expectancy may play an important role. Previous studies that have used stop or no-go signals to manipulate stimulus–stop learning cannot distinguish between stimulus-signal and stimulus-goal associations, and expectancy has not been measured properly. In the present study, participants performed a task that combined features of the go/no-go task and the stop-signal task in which the stop-signal rule changed at the beginning of each block. The go and stop signals were superimposed over 40 task-irrelevant images. Our results show that participants can learn direct associations between images and the stop goal without mediation via the stop signal. Exposure to the image-stop associations influenced task performance during training, and expectancies measured following task completion or measured within the task. But, despite this, we found an effect of stimulus–stop learning on test performance only when the task increased the task-relevance of the images. This could indicate that the influence of stimulus–stop learning on go performance is strongly influenced by attention to both task-relevant and task-irrelevant stimulus features. More generally, our findings suggest a strong interplay between automatic and controlled processes. PMID:26322688

Programming and reprogramming sequence timing following high and low contextual interference practice.

PubMed

Wright, David L; Magnuson, Curt E; Black, Charles B

2005-09-01

Individuals practiced two unique discrete sequence production tasks that differed in their relative time profile in either a blocked or random practice schedule. Each participant was subsequently administered a "precuing" protocol to examine the cost of initially compiling or modifying the plan for an upcoming movement's relative timing. The findings indicated that, in general, random practice facilitated the programming of the required movement timing, and this was accomplished while exhibiting greater accuracy in movement production. Participants exposed to random practice exhibited the greatest motor programming benefit, when a modification to an already prepared movement timing profile was required. When movement timing was only partially constructed prior to the imperative signal, the individuals who were trained in blocked and random practice formats accrued a similar cost to complete the programming process. These data provide additional support for the recent claim of Immink & Wright (2001) that at least some of the benefit from experience in a random as opposed to blocked training context can be localized to superior development and implementation of the motor programming process before executing the movement.

Synchronous acquisition of multi-channel signals by single-channel ADC based on square wave modulation

NASA Astrophysics Data System (ADS)

Yi, Xiaoqing; Hao, Liling; Jiang, Fangfang; Xu, Lisheng; Song, Shaoxiu; Li, Gang; Lin, Ling

2017-08-01

Synchronous acquisition of multi-channel biopotential signals, such as electrocardiograph (ECG) and electroencephalograph, has vital significance in health care and clinical diagnosis. In this paper, we proposed a new method which is using single channel ADC to acquire multi-channel biopotential signals modulated by square waves synchronously. In this method, a specific modulate and demodulate method has been investigated without complex signal processing schemes. For each channel, the sampling rate would not decline with the increase of the number of signal channels. More specifically, the signal-to-noise ratio of each channel is n times of the time-division method or an improvement of 3.01 ×log2n dB, where n represents the number of the signal channels. A numerical simulation shows the feasibility and validity of this method. Besides, a newly developed 8-lead ECG based on the new method has been introduced. These experiments illustrate that the method is practicable and thus is potential for low-cost medical monitors.

Impact of signals and experience on trust and trusting behavior.

PubMed

Chen, Ying-Hueih; Chien, Shu-Hua; Wu, Jyh-Jeng; Tsai, Pei-Yin

2010-10-01

Trust is an essential factor that drives virtual interaction and transactions on the Internet. Researchers have investigated the trust development process, and identified several important factors that form the basis for trust. This research combines the signal perspective and trust theory to examine the impact of market signals and past experience on trust formation and trusting behavior. Three market signals, including brand image, Web-site investment, and privacy policies, are identified and empirically tested to determine their impact on consumer trust. Based on 322 active Web users, the quantitative results suggest that brand image, Web-site investment, privacy policies, and past experience all positively impact trust formation. Furthermore, trust shows a positive effect on Web-site stickiness. Both theoretical and practical implications of the results are also offered.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

Simple simulation training system for short-wave radio station

NASA Astrophysics Data System (ADS)

Tan, Xianglin; Shao, Zhichao; Tu, Jianhua; Qu, Fuqi

2018-04-01

The short-wave radio station is a most important transmission equipment of our signal corps, but in the actual teaching process, which exist the phenomenon of fewer equipment and more students, making the students' short-wave radio operation and practice time is very limited. In order to solve the above problems, to carry out shortwave radio simple simulation training system development is very necessary. This project is developed by combining hardware and software to simulate the voice communication operation and signal principle of shortwave radio station, and can test the signal flow of shortwave radio station. The test results indicate that this system is simple operation, human-machine interface friendly and can improve teaching more efficiency.

Lung Parenchymal Signal Intensity in MRI: A Technical Review with Educational Aspirations Regarding Reversible Versus Irreversible Transverse Relaxation Effects in Common Pulse Sequences.

PubMed

Mulkern, Robert; Haker, Steven; Mamata, Hatsuho; Lee, Edward; Mitsouras, Dimitrios; Oshio, Koichi; Balasubramanian, Mukund; Hatabu, Hiroto

2014-03-01

Lung parenchyma is challenging to image with proton MRI. The large air space results in ~l/5th as many signal-generating protons compared to other organs. Air/tissue magnetic susceptibility differences lead to strong magnetic field gradients throughout the lungs and to broad frequency distributions, much broader than within other organs. Such distributions have been the subject of experimental and theoretical analyses which may reveal aspects of lung microarchitecture useful for diagnosis. Their most immediate relevance to current imaging practice is to cause rapid signal decays, commonly discussed in terms of short T 2 * values of 1 ms or lower at typical imaging field strengths. Herein we provide a brief review of previous studies describing and interpreting proton lung spectra. We then link these broad frequency distributions to rapid signal decays, though not necessarily the exponential decays generally used to define T 2 * values. We examine how these decays influence observed signal intensities and spatial mapping features associated with the most prominent torso imaging sequences, including spoiled gradient and spin echo sequences. Effects of imperfect refocusing pulses on the multiple echo signal decays in single shot fast spin echo (SSFSE) sequences and effects of broad frequency distributions on balanced steady state free precession (bSSFP) sequence signal intensities are also provided. The theoretical analyses are based on the concept of explicitly separating the effects of reversible and irreversible transverse relaxation processes, thus providing a somewhat novel and more general framework from which to estimate lung signal intensity behavior in modern imaging practice.

Lung Parenchymal Signal Intensity in MRI: A Technical Review with Educational Aspirations Regarding Reversible Versus Irreversible Transverse Relaxation Effects in Common Pulse Sequences

PubMed Central

MULKERN, ROBERT; HAKER, STEVEN; MAMATA, HATSUHO; LEE, EDWARD; MITSOURAS, DIMITRIOS; OSHIO, KOICHI; BALASUBRAMANIAN, MUKUND; HATABU, HIROTO

2014-01-01

Lung parenchyma is challenging to image with proton MRI. The large air space results in ~l/5th as many signal-generating protons compared to other organs. Air/tissue magnetic susceptibility differences lead to strong magnetic field gradients throughout the lungs and to broad frequency distributions, much broader than within other organs. Such distributions have been the subject of experimental and theoretical analyses which may reveal aspects of lung microarchitecture useful for diagnosis. Their most immediate relevance to current imaging practice is to cause rapid signal decays, commonly discussed in terms of short T2* values of 1 ms or lower at typical imaging field strengths. Herein we provide a brief review of previous studies describing and interpreting proton lung spectra. We then link these broad frequency distributions to rapid signal decays, though not necessarily the exponential decays generally used to define T2* values. We examine how these decays influence observed signal intensities and spatial mapping features associated with the most prominent torso imaging sequences, including spoiled gradient and spin echo sequences. Effects of imperfect refocusing pulses on the multiple echo signal decays in single shot fast spin echo (SSFSE) sequences and effects of broad frequency distributions on balanced steady state free precession (bSSFP) sequence signal intensities are also provided. The theoretical analyses are based on the concept of explicitly separating the effects of reversible and irreversible transverse relaxation processes, thus providing a somewhat novel and more general framework from which to estimate lung signal intensity behavior in modern imaging practice. PMID:25228852

New method of control of tooth whitening

NASA Astrophysics Data System (ADS)

Angelov, I.; Mantareva, V.; Gisbrecht, A.; Valkanov, S.; Uzunov, Tz.

2010-10-01

New methods of control of tooth bleaching stages through simultaneous measurements of a reflected light and a fluorescence signal are proposed. It is shown that the bleaching process leads to significant changes in the intensity of a scattered signal and also in the shape and intensity of the fluorescence spectra. Experimental data illustrate that the bleaching process causes essential changes in the teeth discoloration in short time as 8-10 min from the beginning of the application procedure. The continuation of the treatment is not necessary moreover the probability of the enamel destroy increases considerably. The proposed optical back control of tooth surface is a base for development of a practical set up to control the duration of the bleaching procedure.

[Situational awareness: you won't see it unless you understand it].

PubMed

Graafland, Maurits; Schijven, Marlies P

2015-01-01

In dynamic, high-risk environments such as the modern operating theatre, healthcare providers are required to identify a multitude of signals correctly and in time. Errors resulting from failure to identify or interpret signals correctly lead to calamities. Medical training curricula focus largely on teaching technical skills and knowledge, not on the cognitive skills needed to interact appropriately with fast-changing, complex environments in practice. The term 'situational awareness' describes the dynamic process of receiving, interpreting and processing information in such dynamic environments. Improving situational awareness in high-risk environments should be part of medical curricula. In addition, the flood of information in high-risk environments should be presented more clearly and effectively. It is important that physicians become more involved in this regard.

Beyond the Garden of Eden: Deep Teacher Professional Development

ERIC Educational Resources Information Center

Samuel, M.

2009-01-01

Becoming a professional teacher is falsely understood to be a simple process: usually consisting of a transference of skills to execute classroom pedagogy or classroom management. This article begins by exploring the many forces which influence the curriculum of teacher education in higher education, signaling the complexity of the practice of…

For operation of the Computer Software Management and Information Center (COSMIC)

NASA Technical Reports Server (NTRS)

Carmon, J. L.

1983-01-01

Computer programs for large systems of normal equations, an interactive digital signal process, structural analysis of cylindrical thrust chambers, swirling turbulent axisymmetric recirculating flows in practical isothermal combustor geometrics, computation of three dimensional combustor performance, a thermal radiation analysis system, transient response analysis, and a software design analysis are summarized.

Research on vibration signal of engine based on subband energy method

NASA Astrophysics Data System (ADS)

Wu, Chunmei; Cui, Feng; Zhao, Yong; Fu, Baohong; Ma, Junchi; Yang, Guihua

2017-04-01

Based on the research of DA462 type engine cylinder and cylinder head vibration signal of the surface, the signal measured in the time domain and frequency domain are analyzed in detail, draw the following conclusions: the analysis of vibration signal of the subband energy method is applied to the engine, the concentration response of each of the motivation band can clearly be seen. Through the analysis we can see that the combustion excitation frequency response from 0k to 1K, the vibration influence on the body piston lateral impact force is mainly concentrated in 2K˜5K frequency range of Hz, valve opening and closing the excitation response frequency is mainly concentrated in the 3K˜4K range of Hz, and thus locating the valve clearance fault. This method is simple, accurate and practical for the post processing and analysis of vibration signals.

The Seismic Tool-Kit (STK): An Open Source Software For Learning the Basis of Signal Processing and Seismology.

NASA Astrophysics Data System (ADS)

Reymond, D.

2016-12-01

We present an open source software project (GNU public license), named STK: Seismic Tool-Kit, that is dedicated mainly for learning signal processing and seismology. The STK project that started in 2007, is hosted by SourceForge.net, and count more than 20000 downloads at the date of writing.The STK project is composed of two main branches:First, a graphical interface dedicated to signal processing (in the SAC format (SAC_ASCII and SAC_BIN): where the signal can be plotted, zoomed, filtered, integrated, derivated, ... etc. (a large variety of IFR and FIR filter is proposed). The passage in the frequency domain via the Fourier transform is used to introduce the estimation of spectral density of the signal , with visualization of the Power Spectral Density (PSD) in linear or log scale, and also the evolutive time-frequency representation (or sonagram). The 3-components signals can be also processed for estimating their polarization properties, either for a given window, or either for evolutive windows along the time. This polarization analysis is useful for extracting the polarized noises, differentiating P waves, Rayleigh waves, Love waves, ... etc. Secondly, a panel of Utilities-Program are proposed for working in a terminal mode, with basic programs for computing azimuth and distance in spherical geometry, inter/auto-correlation, spectral density, time-frequency for an entire directory of signals, focal planes, and main components axis, radiation pattern of P waves, Polarization analysis of different waves (including noise), under/over-sampling the signals, cubic-spline smoothing, and linear/non linear regression analysis of data set. STK is developed in C/C++, mainly under Linux OS, and it has been also partially implemented under MS-Windows. STK has been used in some schools for viewing and plotting seismic records provided by IRIS, and it has been used as a practical support for teaching the basis of signal processing. Useful links:http://sourceforge.net/projects/seismic-toolkit/http://sourceforge.net/p/seismic-toolkit/wiki/browse_pages/

System theory in industrial patient monitoring: an overview.

PubMed

Baura, G D

2004-01-01

Patient monitoring refers to the continuous observation of repeating events of physiologic function to guide therapy or to monitor the effectiveness of interventions, and is used primarily in the intensive care unit and operating room. Commonly processed signals are the electrocardiogram, intraarterial blood pressure, arterial saturation of oxygen, and cardiac output. To this day, the majority of physiologic waveform processing in patient monitors is conducted using heuristic curve fitting. However in the early 1990s, a few enterprising engineers and physicians began using system theory to improve their core processing. Applications included improvement of signal-to-noise ratio, either due to low signal levels or motion artifact, and improvement in feature detection. The goal of this mini-symposium is to review the early work in this emerging field, which has led to technologic breakthroughs. In this overview talk, the process of system theory algorithm research and development is discussed. Research for industrial monitors involves substantial data collection, with some data used for algorithm training and the remainder used for validation. Once the algorithms are validated, they are translated into detailed specifications. Development then translates these specifications into DSP code. The DSP code is verified and validated per the Good Manufacturing Practices mandated by FDA.

Biomolecular logic systems: applications to biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Katz, Evgeny

2014-05-01

The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines

NASA Astrophysics Data System (ADS)

Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho

2016-03-01

We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.

Eddy current testing for blade edge micro cracks of aircraft engine

NASA Astrophysics Data System (ADS)

Zhang, Wei-min; Xu, Min-dong; Gao, Xuan-yi; Jin, Xin; Qin, Feng

2017-10-01

Based on the problems of low detection efficiency in the micro cracks detection of aircraft engine blades, a differential excitation eddy current testing system was designed and developed. The function and the working principle of the system were described, the problems which contained the manufacture method of simulated cracks, signal generating, signal processing and the signal display method were described. The detection test was carried out by taking a certain model aircraft engine blade with simulated cracks as a tested specimen. The test data was processed by digital low-pass filter in the computer and the crack signals of time domain display and Lissajous figure display were acquired. By comparing the test results, it is verified that Lissajous figure display shows better performance compared to time domain display when the crack angle is small. The test results show that the eddy current testing system designed in this paper is feasible to detect the micro cracks on the aeroengine blade and can effectively improve the detection efficiency of micro cracks in the practical detection work.

Far-field DOA estimation and source localization for different scenarios in a distributed sensor network

NASA Astrophysics Data System (ADS)

Asgari, Shadnaz

Recent developments in the integrated circuits and wireless communications not only open up many possibilities but also introduce challenging issues for the collaborative processing of signals for source localization and beamforming in an energy-constrained distributed sensor network. In signal processing, various sensor array processing algorithms and concepts have been adopted, but must be further tailored to match the communication and computational constraints. Sometimes the constraints are such that none of the existing algorithms would be an efficient option for the defined problem and as the result; the necessity of developing a new algorithm becomes undeniable. In this dissertation, we present the theoretical and the practical issues of Direction-Of-Arrival (DOA) estimation and source localization using the Approximate-Maximum-Likelihood (AML) algorithm for different scenarios. We first investigate a robust algorithm design for coherent source DOA estimation in a limited reverberant environment. Then, we provide a least-square (LS) solution for source localization based on our newly proposed virtual array model. In another scenario, we consider the determination of the location of a disturbance source which emits both wideband acoustic and seismic signals. We devise an enhanced AML algorithm to process the data collected at the acoustic sensors. For processing the seismic signals, two distinct algorithms are investigated to determine the DOAs. Then, we consider a basic algorithm for fusion of the results yielded by the acoustic and seismic arrays. We also investigate the theoretical and practical issues of DOA estimation in a three-dimensional (3D) scenario. We show that the performance of the proposed 3D AML algorithm converges to the Cramer-Rao Bound. We use the concept of an isotropic array to reduce the complexity of the proposed algorithm by advocating a decoupled 3D version. We also explore a modified version of the decoupled 3D AML algorithm which can be used for DOA estimation with non-isotropic arrays. In this dissertation, for each scenario, efficient numerical implementations of the corresponding AML algorithm are derived and applied into a real-time sensor network testbed. Extensive simulations as well as experimental results are presented to verify the effectiveness of the proposed algorithms.

Brain activation associated with practiced left hand mirror writing.

PubMed

Kushnir, T; Arzouan, Y; Karni, A; Manor, D

2013-04-01

Mirror writing occurs in healthy children, in various pathologies and occasionally in healthy adults. There are only scant experimental data on the underlying brain processes. Eight, right-handed, healthy young adults were scanned (BOLD-fMRI) before and after practicing left-hand mirror-writing (lh-MW) over seven sessions. They wrote dictated words, using either the right hand with regularly oriented writing or lh-MW. An MRI compatible stylus-point recording system was used and online visual feedback was provided. Practice resulted in increased speed and readability of lh-MW but the number of movement segments was unchanged. Post-training signal increases occurred in visual, right lateral and medial premotor areas, and in right anterior and posterior peri-sylvian areas corresponding to language areas. These results suggest that lh-MW may constitute a latent ability that can be reinstated by a relatively brief practice experience. Concurrently, right hemisphere language processing areas may emerge, reflecting perhaps a reduction in trans-hemispheric suppression. Copyright © 2013 Elsevier Inc. All rights reserved.

Illuminating the Signals Job Seekers Receive from an Employer's Community Involvement and Environmental Sustainability Practices: Insights into Why Most Job Seekers Are Attracted, Others Are Indifferent, and a Few Are Repelled

PubMed Central

Jones, David A.; Willness, Chelsea R.; Heller, Kristin W.

2016-01-01

Evidence shows that job seekers tend to be attracted to employers known for their corporate social responsibility (CSR), but relatively little is known about the underlying psychological processes. Moreover, the literature is silent about whether and why some job seekers are unaffected, or even repelled by, an employer's CSR. We conducted a substantive replication of recent empirical support for three signal-based mechanisms by adapting the experimental manipulation used in a prior study while employing an alternative approach to analyzing a distinctly different type of data. We also extended prior work by examining other possible explanatory mechanisms and exploring potentially negative reactions to CSR. Using signaling theory as an overarching framework, we assessed research questions and tested hypotheses grounded in theories of employee recruitment and the psychology of CSR, specifying how an employer's CSR practices send signals from which job seekers draw inferences about unknown working conditions, thereby affecting their attraction to the employer. Study participants (N = 108) reviewed the webpages of two hiring companies and responded to open-ended questions about each employer. We content-analyzed written responses pertaining to one employer's webpages in which we embedded an experimental manipulation of information about the employer's community involvement or its environmentally sustainable practices. The results supported hypotheses that corroborate prior evidence for the “perceived value fit” and “expected employee treatment” mechanisms, and provided some, but relatively limited, support for the “anticipated pride” mechanism. Assessment of research questions highlighted previously undiscovered signal-based mechanisms that might help explain job seekers' attraction to CSR (e.g., inferences about the employer's positive work environment and financial standing, and the nature of its employees). Results also showed that a few people were less attracted because of the employer's CSR practices. Analyses among those individuals, combined with one-third of the sample who reported their attraction was unaffected by the employer's CSR, provided insights about when and why CSR fails to enhance attraction, such as when job seekers focus on other priorities, or are deeply skeptical and cynical about the employer's CSR. We discuss the implications for advancing a signal-based theory of CSR and employee recruitment, and recruitment practice. PMID:27064985

Illuminating the Signals Job Seekers Receive from an Employer's Community Involvement and Environmental Sustainability Practices: Insights into Why Most Job Seekers Are Attracted, Others Are Indifferent, and a Few Are Repelled.

PubMed

Jones, David A; Willness, Chelsea R; Heller, Kristin W

2016-01-01

Evidence shows that job seekers tend to be attracted to employers known for their corporate social responsibility (CSR), but relatively little is known about the underlying psychological processes. Moreover, the literature is silent about whether and why some job seekers are unaffected, or even repelled by, an employer's CSR. We conducted a substantive replication of recent empirical support for three signal-based mechanisms by adapting the experimental manipulation used in a prior study while employing an alternative approach to analyzing a distinctly different type of data. We also extended prior work by examining other possible explanatory mechanisms and exploring potentially negative reactions to CSR. Using signaling theory as an overarching framework, we assessed research questions and tested hypotheses grounded in theories of employee recruitment and the psychology of CSR, specifying how an employer's CSR practices send signals from which job seekers draw inferences about unknown working conditions, thereby affecting their attraction to the employer. Study participants (N = 108) reviewed the webpages of two hiring companies and responded to open-ended questions about each employer. We content-analyzed written responses pertaining to one employer's webpages in which we embedded an experimental manipulation of information about the employer's community involvement or its environmentally sustainable practices. The results supported hypotheses that corroborate prior evidence for the "perceived value fit" and "expected employee treatment" mechanisms, and provided some, but relatively limited, support for the "anticipated pride" mechanism. Assessment of research questions highlighted previously undiscovered signal-based mechanisms that might help explain job seekers' attraction to CSR (e.g., inferences about the employer's positive work environment and financial standing, and the nature of its employees). Results also showed that a few people were less attracted because of the employer's CSR practices. Analyses among those individuals, combined with one-third of the sample who reported their attraction was unaffected by the employer's CSR, provided insights about when and why CSR fails to enhance attraction, such as when job seekers focus on other priorities, or are deeply skeptical and cynical about the employer's CSR. We discuss the implications for advancing a signal-based theory of CSR and employee recruitment, and recruitment practice.

The Time-Domain Matched Filter and the Spectral-Domain Matched Filter in 1-Dimensional NMR Spectroscopy.

PubMed

Spencer, Richard G

2010-09-01

A type of "matched filter" (MF), used extensively in the processing of one-dimensional spectra, is defined by multiplication of a free-induction decay (FID) by a decaying exponential with the same time constant as that of the FID. This maximizes, in a sense to be defined, the signal-to-noise ratio (SNR) in the spectrum obtained after Fourier transformation. However, a different entity known also as the matched filter was introduced by van Vleck in the context of pulse detection in the 1940's and has become widely integrated into signal processing practice. These two types of matched filters appear to be quite distinct. In the NMR case, the "filter", that is, the exponential multiplication, is defined by the characteristics of, and applied to, a time domain signal in order to achieve improved SNR in the spectral domain. In signal processing, the filter is defined by the characteristics of a signal in the spectral domain, and applied in order to improve the SNR in the temporal (pulse) domain. We reconcile these two distinct implementations of the matched filter, demonstrating that the NMR "matched filter" is a special case of the matched filter more rigorously defined in the signal processing literature. In addition, two limitations in the use of the MF are highlighted. First, application of the MF distorts resonance ratios as defined by amplitudes, although not as defined by areas. Second, the MF maximizes SNR with respect to resonance amplitude, while intensities are often more appropriately defined by areas. Maximizing the SNR with respect to area requires a somewhat different approach to matched filtering.

Nanovesicle-based bioelectronic nose platform mimicking human olfactory signal transduction.

PubMed

Jin, Hye Jun; Lee, Sang Hun; Kim, Tae Hyun; Park, Juhun; Song, Hyun Seok; Park, Tai Hyun; Hong, Seunghun

2012-05-15

We developed a nanovesicle-based bioelectronic nose (NBN) that could recognize a specific odorant and mimic the receptor-mediated signal transmission of human olfactory systems. To build an NBN, we combined a single-walled carbon nanotube-based field effect transistor with cell-derived nanovesicles containing human olfactory receptors and calcium ion signal pathways. Importantly, the NBN took advantages of cell signal pathways for sensing signal amplification, enabling ≈ 100 times better sensitivity than that of previous bioelectronic noses based on only olfactory receptor protein and carbon nanotube transistors. The NBN sensors exhibited a human-like selectivity with single-carbon-atomic resolution and a high sensitivity of 1 fM detection limit. Moreover, this sensor platform could mimic a receptor-meditated cellular signal transmission in live cells. This sensor platform can be utilized for the study of molecular recognition and biological processes occurring at cell membranes and also for various practical applications such as food screening and medical diagnostics. Copyright © 2012 Elsevier B.V. All rights reserved.

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

PubMed Central

Mora-Jiménez, Inmaculada; Ramos-López, Javier; Quintanilla Fernández, Teresa; García-García, Antonio; Díez-Mazuela, Daniel; García-Alberola, Arcadi

2018-01-01

Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain. PMID:29494497

Humic Substances: Determining Potential Molecular Regulatory Processes in Plants

PubMed Central

Shah, Zahid Hussain; Rehman, Hafiz M.; Akhtar, Tasneem; Alsamadany, Hameed; Hamooh, Bahget T.; Mujtaba, Tahir; Daur, Ihsanullah; Al Zahrani, Yahya; Alzahrani, Hind A. S.; Ali, Shawkat; Yang, Seung H.; Chung, Gyuhwa

2018-01-01

Humic substances (HSs) have considerable effects on soil fertility and crop productivity owing to their unique physiochemical and biochemical properties, and play a vital role in establishing biotic and abiotic interactions within the plant rhizosphere. A comprehensive understanding of the mode of action and tissue distribution of HS is, however, required, as this knowledge could be useful for devising advanced rhizospheric management practices. These substances trigger various molecular processes in plant cells, and can strengthen the plant’s tolerance to various kinds of abiotic stresses. HS manifest their effects in cells through genetic, post-transcriptional, and post-translational modifications of signaling entities that trigger different molecular, biochemical, and physiological processes. Understanding of such fundamental mechanisms will provide a better perspective for defining the cues and signaling crosstalk of HS that mediate various metabolic and hormonal networks operating in plant systems. Various regulatory activities and distribution strategies of HS have been discussed in this review. PMID:29593751

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System.

PubMed

Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug

2018-04-30

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

Design of Moisture Content Detection System

NASA Astrophysics Data System (ADS)

Wang, W. C.; Wang, L.

In this paper, a method for measuring the moisture content of grain was presented based on single chip microcomputer and capacitive sensor. The working principle of measuring moisture content is introduced and a concentric cylinder type of capacitive sensor is designed, the signal processing circuits of system are described in details. System is tested in practice and discussions are made on the various factors affecting the capacitive measuring of grain moisture based on the practical experiments, experiment results showed that the system has high measuring accuracy and good controlling capacity.

A new similarity index for nonlinear signal analysis based on local extrema patterns

NASA Astrophysics Data System (ADS)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.

Remote photoacoustic detection of liquid contamination of a surface.

PubMed

Perrett, Brian; Harris, Michael; Pearson, Guy N; Willetts, David V; Pitter, Mark C

2003-08-20

A method for the remote detection and identification of liquid chemicals at ranges of tens of meters is presented. The technique uses pulsed indirect photoacoustic spectroscopy in the 10-microm wavelength region. Enhanced sensitivity is brought about by three main system developments: (1) increased laser-pulse energy (150 microJ/pulse), leading to increased strength of the generated photoacoustic signal; (2) increased microphone sensitivity and improved directionality by the use of a 60-cm-diameter parabolic dish; and (3) signal processing that allows improved discrimination of the signal from noise levels through prior knowledge of the pulse shape and pulse-repetition frequency. The practical aspects of applying the technique in a field environment are briefly examined, and possible applications of this technique are discussed.

Analysis of automobile engine cylinder pressure and rotation speed from engine body vibration signal

NASA Astrophysics Data System (ADS)

Wang, Yuhua; Cheng, Xiang; Tan, Haishu

2016-01-01

In order to improve the engine vibration signal process method for the engine cylinder pressure and engine revolution speed measurement instrument, the engine cylinder pressure varying with the engine working cycle process has been regarded as the main exciting force for the engine block forced vibration. The forced vibration caused by the engine cylinder pressure presents as a low frequency waveform which varies with the cylinder pressure synchronously and steadily in time domain and presents as low frequency high energy discrete humorous spectrum lines in frequency domain. The engine cylinder pressure and the rotation speed can been extract form the measured engine block vibration signal by low-pass filtering analysis in time domain or by FFT analysis in frequency domain, the low-pass filtering analysis in time domain is not only suitable for the engine in uniform revolution condition but also suitable for the engine in uneven revolution condition. That provides a practical and convenient way to design motor revolution rate and cylinder pressure measurement instrument.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique

PubMed Central

Ardila-Rey, Jorge Alfredo; Montaña, Johny; Schurch, Roger; Covolan Ulson, José Alfredo; Bani, Nurul Aini

2018-01-01

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals. PMID:29596337

Mathematical models utilized in the retrieval of displacement information encoded in fringe patterns

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Lamberti, Luciano

2016-02-01

All the techniques that measure displacements, whether in the range of visible optics or any other form of field methods, require the presence of a carrier signal. A carrier signal is a wave form modulated (modified) by an input, deformation of the medium. A carrier is tagged to the medium under analysis and deforms with the medium. The wave form must be known both in the unmodulated and the modulated conditions. There are two basic mathematical models that can be utilized to decode the information contained in the carrier, phase modulation or frequency modulation, both are closely connected. Basic problems connected to the detection and recovery of displacement information that are common to all optical techniques will be analyzed in this paper, focusing on the general theory common to all the methods independently of the type of signal utilized. The aspects discussed are those that have practical impact in the process of data gathering and data processing.

Signal processing and calibration procedures for in situ diode-laser absorption spectroscopy.

PubMed

Werle, P W; Mazzinghi, P; D'Amato, F; De Rosa, M; Maurer, K; Slemr, F

2004-07-01

Gas analyzers based on tunable diode-laser spectroscopy (TDLS) provide high sensitivity, fast response and highly specific in situ measurements of several atmospheric trace gases simultaneously. Under optimum conditions even a shot noise limited performance can be obtained. For field applications outside the laboratory practical limitations are important. At ambient mixing ratios below a few parts-per-billion spectrometers become more and more sensitive towards noise, interference, drift effects and background changes associated with low level signals. It is the purpose of this review to address some of the problems which are encountered at these low levels and to describe a signal processing strategy for trace gas monitoring and a concept for in situ system calibration applicable for tunable diode-laser spectroscopy. To meet the requirement of quality assurance for field measurements and monitoring applications, procedures to check the linearity according to International Standard Organization regulations are described and some measurements of calibration functions are presented and discussed.

Application of digital signal processing methods for the diagnosis of respiration disorders during sleep with the use of plethysmographic wave analysis

NASA Astrophysics Data System (ADS)

Hatlinski, Grzegorz J.; Kornacki, Witold; Kukwa, Andrzej; Dobrowiecka, Bozena; Pikiel, Marek

2004-07-01

This paper proposes non-invasive solution to the problem of sleep apnea diagnosis especially in small children when sudden death syndrome is suspected. Plethysmographic wave analysis and digital signal processing algorithms are applied in order to find the effect invoked by respiratory movements of sleeping patients so as to diagnose the sleep apnea syndrome. The practical results of finding solution to problems mentioned above will be the possibility of algorithms implementation in a portable intelligent measurement system with a non-invasive monitoring of respiratory action. It works without any disturbances of sleep and respiratory movements especially in small children what could make possible in the future when continuous monitoring were applied to prevent sudden death syndrome occurrence.

Inhomogeneous Poisson process rate function inference from dead-time limited observations.

PubMed

Verma, Gunjan; Drost, Robert J

2017-05-01

The estimation of an inhomogeneous Poisson process (IHPP) rate function from a set of process observations is an important problem arising in optical communications and a variety of other applications. However, because of practical limitations of detector technology, one is often only able to observe a corrupted version of the original process. In this paper, we consider how inference of the rate function is affected by dead time, a period of time after the detection of an event during which a sensor is insensitive to subsequent IHPP events. We propose a flexible nonparametric Bayesian approach to infer an IHPP rate function given dead-time limited process realizations. Simulation results illustrate the effectiveness of our inference approach and suggest its ability to extend the utility of existing sensor technology by permitting more accurate inference on signals whose observations are dead-time limited. We apply our inference algorithm to experimentally collected optical communications data, demonstrating the practical utility of our approach in the context of channel modeling and validation.

Real-time optical fiber digital speckle pattern interferometry for industrial applications

NASA Astrophysics Data System (ADS)

Chan, Robert K.; Cheung, Y. M.; Lo, C. H.; Tam, T. K.

1997-03-01

There is current interest, especially in the industrial sector, to use the digital speckle pattern interferometry (DSPI) technique to measure surface stress. Indeed, many publications in the subject are evident of the growing interests in the field. However, to bring the technology to industrial use requires the integration of several emerging technologies, viz. optics, feedback control, electronics, imaging processing and digital signal processing. Due to the highly interdisciplinary nature of the technique, successful implementation and development require expertise in all of the fields. At Baptist University, under the funding of a major industrial grant, we are developing the technology for the industrial sector. Our system fully exploits optical fibers and diode lasers in the design to enable practical and rugged systems suited for industrial applications. Besides the development in optics, we have broken away from the reliance of a microcomputer PC platform for both image capture and processing, and have developed a digital signal processing array system that can handle simultaneous and independent image capture/processing with feedback control. The system, named CASPA for 'cascadable architecture signal processing array,' is a third generation development system that utilizes up to 7 digital signal processors has proved to be a very powerful system. With our CASPA we are now in a better position to developing novel optical measurement systems for industrial application that may require different measurement systems to operate concurrently and requiring information exchange between the systems. Applications in mind such as simultaneous in-plane and out-of-plane DSPI image capture/process, vibrational analysis with interactive DSPI and phase shifting control of optical systems are a few good examples of the potentials.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis.

PubMed

Liu, Jinjun; Leng, Yonggang; Lai, Zhihui; Fan, Shengbo

2018-04-25

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method.

Mastication noise reduction method for fully implantable hearing aid using piezo-electric sensor.

PubMed

Na, Sung Dae; Lee, Gihyoun; Wei, Qun; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam

2017-07-20

Fully implantable hearing devices (FIHDs) can be affected by generated biomechanical noise such as mastication noise. To reduce the mastication noise using a piezo-electric sensor, the mastication noise is measured with the piezo-electric sensor, and noise reduction is practiced by the energy difference. For the experiment on mastication noise, a skull model was designed using artificial skull model and a piezo-electric sensor that can measure the vibration signals better than other sensors. A 1 kHz pure-tone sound through a standard speaker was applied to the model while the lower jawbone of the model was moved in a masticatory fashion. The correlation coefficients and signal-to-noise ratio (SNR) before and after application of the proposed method were compared. It was found that the signal-to-noise ratio and correlation coefficients increased by 4.48 dB and 0.45, respectively. The mastication noise is measured by piezo-electric sensor as the mastication noise that occurred during vibration. In addition, the noise was reduced by using the proposed method in conjunction with MATLAB. In order to confirm the performance of the proposed method, the correlation coefficients and signal-to-noise ratio before and after signal processing were calculated. In the future, an implantable microphone for real-time processing will be developed.

Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring

PubMed Central

Sun, Jiedi; Yu, Yang; Wen, Jiangtao

2017-01-01

Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN. The compressed data acquisition is realized by projection transformation and can greatly reduce the data volume, which needs the nodes to process and transmit. The reconstruction of original signals is achieved in the host computer by complicated algorithms. The bearing vibration signals not only exhibit the sparsity property, but also have specific structures. This paper introduced the block sparse Bayesian learning (BSBL) algorithm which works by utilizing the block property and inherent structures of signals to reconstruct CS sparsity coefficients of transform domains and further recover the original signals. By using the BSBL, CS reconstruction can be improved remarkably. Experiments and analyses showed that BSBL method has good performance and is suitable for practical bearing-condition monitoring. PMID:28635623

Coherent detection and digital signal processing for fiber optic communications

NASA Astrophysics Data System (ADS)

Ip, Ezra

The drive towards higher spectral efficiency in optical fiber systems has generated renewed interest in coherent detection. We review different detection methods, including noncoherent, differentially coherent, and coherent detection, as well as hybrid detection methods. We compare the modulation methods that are enabled and their respective performances in a linear regime. An important system parameter is the number of degrees of freedom (DOF) utilized in transmission. Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency as it uses all four available DOF contained in the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Software based receivers benefit from the robustness of DSP, flexibility in design, and ease of adaptation to time-varying channels. Linear impairments, including chromatic dispersion (CD) and polarization-mode dispersion (PMD), can be compensated quasi-exactly using finite impulse response filters. In practical systems, sampling the received signal at 3/2 times the symbol rate is sufficient to enable an arbitrary amount of CD and PMD to be compensated for a sufficiently long equalizer whose tap length scales linearly with transmission distance. Depending on the transmitted constellation and the target bit error rate, the analog-to-digital converter (ADC) should have around 5 to 6 bits of resolution. Digital coherent receivers are naturally suited for the implementation of feedforward carrier recovery, which has superior linewidth tolerance than phase-locked loops, and does not suffer from feedback delay constraints. Differential bit encoding can be used to prevent catastrophic receiver failure due to cycle slips. In systems where nonlinear effects are concentrated mostly at fiber locations with small accumulated dispersion, nonlinear phase de-rotation is a low-complexity algorithm that can partially mitigate nonlinear effects. For systems with arbitrary dispersion maps, however, backpropagation is the only universal technique that can jointly compensate dispersion and fiber nonlinearity. Backpropagation requires solving the nonlinear Schrodinger equation at the receiver, and has high computational cost. Backpropagation is most effective when dispersion compensation fibers are removed, and when signal processing is performed at three times oversampling. Backpropagation can improve system performance and increase transmission distance. With anticipated advances in analog-to-digital converters and integrated circuit technology, DSP-based coherent receivers at bit rates up to 100 Gb/s should become practical in the near future.

Signal systems asset management state-of-the-practice review

DOT National Transportation Integrated Search

2004-04-01

The purpose of this project is to obtain a better understanding of operations-level asset management by examining the specific case of signal systems. Key products will include: a synthesis of existing signal systems asset management practices; a gen...

Feasibility of an ultra-low power digital signal processor platform as a basis for a fully implantable brain-computer interface system.

PubMed

Wang, Po T; Gandasetiawan, Keulanna; McCrimmon, Colin M; Karimi-Bidhendi, Alireza; Liu, Charles Y; Heydari, Payam; Nenadic, Zoran; Do, An H

2016-08-01

A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g. electrocorticogram) and translate them into control commands for external prostheses. The feasibility of such a system was tested by implementing its benchtop analogue, centered around a commercial, ultra-low power (ULP) digital signal processor (DSP, TMS320C5517, Texas Instruments). A suite of signal processing and BCI algorithms, including (de)multiplexing, Fast Fourier Transform, power spectral density, principal component analysis, linear discriminant analysis, Bayes rule, and finite state machine was implemented and tested in the DSP. The system's signal acquisition fidelity was tested and characterized by acquiring harmonic signals from a function generator. In addition, the BCI decoding performance was tested, first with signals from a function generator, and subsequently using human electroencephalogram (EEG) during eyes opening and closing task. On average, the system spent 322 ms to process and analyze 2 s of data. Crosstalk (<;-65 dB) and harmonic distortion (~1%) were minimal. Timing jitter averaged 49 μs per 1000 ms. The online BCI decoding accuracies were 100% for both function generator and EEG data. These results show that a complex BCI algorithm can be executed on an ULP DSP without compromising performance. This suggests that the proposed hardware platform may be used as a basis for future, fully implantable BCI systems.

The BEFWM system for detection and phase conjugation of a weak laser beam

NASA Astrophysics Data System (ADS)

Khizhnyak, Anatoliy; Markov, Vladimir

2007-09-01

Real environmental conditions, such as atmospheric turbulence and aero-optics effects, make practical implementation of the object-in-the-loop (TIL) algorithm a very difficult task, especially when the system is set to operate with a signal from the diffuse surface image-resolved object. The problem becomes even more complex since for the remote object the intensity of the returned signal is extremely low. This presentation discusses the results of an analysis and experimental verification of a thresholdless coherent signal receiving system, capable not only in high-sensitivity detection of an ultra weak object-scattered light, but also in its high-gain amplification and phase conjugation. The process of coherent detection by using the Brillouin Enhanced Four Wave Mixing (BEFWM) enables retrieval of complete information on the received signal, including accurate measurement of its wavefront. This information can be used for direct real-time control of the adaptive mirror.

A unified formulation of dichroic signals using the Borrmann effect and twisted photon beams.

PubMed

Collins, Stephen P; Lovesey, Stephen W

2018-05-21

Dichroic X-ray signals derived from the Borrmann effect and a twisted photon beam with topological charge l = 1 are formulated with an effective wavevector. The unification applies for non-magnetic and magnetic materials. Electronic degrees of freedom associated with an ion are encapsulated in multipoles previously used to interpret conventional dichroism and Bragg diffraction enhanced by an atomic resonance. A dichroic signal exploiting the Borrmann effect with a linearly polarized beam presents charge-like multipoles that include a hexadecapole. A difference between dichroic signals obtained with a twisted beam carrying spin polarization (circular polarization) and opposite winding numbers presents charge-like atomic multipoles, whereas a twisted beam carrying linear polarization alone presents magnetic (time-odd) multipoles. Charge-like multipoles include a quadrupole, and magnetic multipoles include a dipole and an octupole. We discuss the practicalities and relative merits of spectroscopy exploiting the two remarkably closely-related processes. Signals using beams with topological charges l ≥ 2 present additional atomic multipoles.

Bioelectronic Device Mimicking Human Sensory System based on Nanovesicle-Carbon Nanotube Hybrid Structure

NASA Astrophysics Data System (ADS)

Kim, Daesan; Jin, Hye; Lee, San; Kim, Tae; Park, Juhun; Song, Hyun; Park, Tai; Hong, Seunghun

2013-03-01

We have developed a nanovesicle-based bioelectronic nose (NBN) that could mimic the receptor-mediated signal transmission of human olfactory systems and recognize a specific odorant. The NBN was comprised of a single-walled carbon nanotube (CNT)-based field effect transistor and cell-derived nanovesicles containing human olfactory receptors and calcium ion signal pathways. Importantly, the NBN took advantages of cell signal pathways for sensing signal amplification. It enabled ~100 times higher sensitivity than that of previous bioelectronic noses based on only olfactory receptor protein and CNT transistors. The NBN sensors exhibited a high sensitivity of 1 fM detection limit and a human-like selectivity with single-carbon-atomic resolution. Furthermore, these sensors could mimic a receptor-mediated cellular signal transmission in live cells. This versatile sensor platform should be useful for the study of molecular recognition and biological processes on cell membranes and also for various practical applications such as food conditioning and medical diagnostics.

A long distance voice transmission system based on the white light LED

NASA Astrophysics Data System (ADS)

Tian, Chunyu; Wei, Chang; Wang, Yulian; Wang, Dachi; Yu, Benli; Xu, Feng

2017-10-01

A long distance voice transmission system based on a visible light communication technology (VLCT) is proposed in the paper. Our proposed system includes transmitter, receiver and the voice signal processing of single chip microcomputer. In the compact-sized LED transmitter, we use on-off-keying and not-return-to-zero (OOK-NRZ) to easily realize high speed modulation, and then systematic complexity is reduced. A voice transmission system, which possesses the properties of the low-noise and wide modulation band, is achieved by the design of high efficiency receiving optical path and using filters to reduce noise from the surrounding light. To improve the speed of the signal processing, we use single chip microcomputer to code and decode voice signal. Furthermore, serial peripheral interface (SPI) is adopted to accurately transmit voice signal data. The test results of our proposed system show that the transmission distance of this system is more than100 meters with the maximum data rate of 1.5 Mbit/s and a SNR of 30dB. This system has many advantages, such as simple construction, low cost and strong practicality. Therefore, it has extensive application prospect in the fields of the emergency communication and indoor wireless communication, etc.

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language

PubMed Central

Narayanan, Shrikanth; Georgiou, Panayiotis G.

2013-01-01

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion. PMID:24039277

A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar

PubMed Central

Kim, Bongseok; Kim, Sangdong; Lee, Jonghun

2018-01-01

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment. PMID:29758016

Design and implementation of a sigma delta technology based pulse oximeter's acquisition stage

NASA Astrophysics Data System (ADS)

Rossi, E. E.; Peñalva, A.; Schaumburg, F.

2011-12-01

Pulse oximetry is a widely used tool in medical practice for estimating patient's fraction of hemoglobin bonded to oxygen. Conventional oximetry presents limitations when changes in the baseline, or low amplitude of signals involved occur. The aim of this paper is to simultaneously solve these constraints and to simplify the circuitry needed, by using ΣΔ technology. For this purpose, a board for the acquisition of the needed signals was developed, together with a PC managed software which controls it, and displays and processes in real time the information acquired. Also laboratory and field tests where designed and executed to verify the performance of this equipment in adverse situations. A simple, robust and economic instrument was achieved, capable of obtaining signals even in situations where conventional oximetry fails.

Out-Phased Array Linearized Signaling (OPALS): A Practical Approach to Physical Layer Encryption

DTIC Science & Technology

2015-10-26

Out-Phased Array Linearized Signaling ( OPALS ): A Practical Approach to Physical Layer Encryption Eric Tollefson, Bruce R. Jordan Jr., and Joseph D... OPALS ) which provides a practical approach to physical-layer encryption through spatial masking. Our approach modifies just the transmitter to employ...of the channel. With Out-Phased Array Linearized Signaling ( OPALS ), we propose a new masking technique that has some advantages of each of the

The practice of pre-marketing safety assessment in drug development.

PubMed

Chuang-Stein, Christy; Xia, H Amy

2013-01-01

The last 15 years have seen a substantial increase in efforts devoted to safety assessment by statisticians in the pharmaceutical industry. While some of these efforts were driven by regulations and public demand for safer products, much of the motivation came from the realization that there is a strong need for a systematic approach to safety planning, evaluation, and reporting at the program level throughout the drug development life cycle. An efficient process can help us identify safety signals early and afford us the opportunity to develop effective risk minimization plan early in the development cycle. This awareness has led many pharmaceutical sponsors to set up internal systems and structures to effectively conduct safety assessment at all levels (patient, study, and program). In addition to process, tools have emerged that are designed to enhance data review and pattern recognition. In this paper, we describe advancements in the practice of safety assessment during the premarketing phase of drug development. In particular, we share examples of safety assessment practice at our respective companies, some of which are based on recommendations from industry-initiated working groups on best practice in recent years.

Quantitative change of EEG and respiration signals during mindfulness meditation.

PubMed

Ahani, Asieh; Wahbeh, Helane; Nezamfar, Hooman; Miller, Meghan; Erdogmus, Deniz; Oken, Barry

2014-05-14

This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies.

Recessive palmoplantar keratodermas: a tale of wings, hands, hair and cancer.

PubMed

Van Steensel, M A M

2010-12-01

The palmoplantar keratodermas (PPKs) are a heterogeneous group of disorders of cornification affecting the palms and soles. Of late, a number of rare, recessive PPKs such as odonto-onycho-dermal dysplasia have been elucidated. Surprisingly, these results indicate that correct palmoplantar keratinization depends on intact Wingless (WNT) signalling. WNT was originally discovered in the fruit fly where it is required for wing morphogenesis. This ancient signalling pathway is now emerging as a master regulator of differentiation in a variety of tissues, including the intestine and the hair follicle. It is also becoming increasingly clear that deregulation of WNT signalling is involved in neoplasia. Thus, a single pathway unites several seemingly disparate processes and disorders. The keratodermas are emerging as model systems in which to study WNT signalling. Moreover, as agents that are in the dermatological arsenal can modulate WNT signalling, some insight into its workings is of importance to the practicing dermatologist. In this review, I outline how WNT signalling is involved in epidermal differentiation and skin cancer and what these new insights mean for everyday dermatology.

Quantitative change of EEG and respiration signals during mindfulness meditation

PubMed Central

2014-01-01

Background This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. Methods EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Results Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Conclusion Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies. PMID:24939519

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

Signal enhancement for gradient reverse-phase high-performance liquid chromatography-electrospray ionization mass spectrometry analysis with trifluoroacetic and other strong acid modifiers by postcolumn addition of propionic acid and isopropanol.

PubMed

Kuhlmann, F E; Apffel, A; Fischer, S M; Goldberg, G; Goodley, P C

1995-12-01

Trifluoroacetic acid (TFA) and other volatile strong acids, used as modifiers in reverse-phase high-performance liquid chromatography, cause signal suppression for basic compounds when analyzed by electrospray ionization mass spectrometry (ESI-MS). Evidence is presented that signal suppression is caused by strong ion pairing between the TFA anion and the protonated sample cation of basic sample molecules. The ion-pairing process "masks" the protonated sample cations from the ESI-MS electric fields by rendering them "neutral. " Weakly basic molecules are not suppressed by this process. The TFA signal suppression effect is independent from the well-known spray problem that electrospray has with highly aqueous solutions that contain TFA. This previously reported spray problem is caused by the high conductivity and surface tension of aqueous TFA solutions. A practical method to enhance the signal for most basic analytes in the presence of signal-suppressing volatile strong acids has been developed. The method employs postcolumn addition of a solution of 75% propionic acid and 25% isopropanol in a ratio 1:2 to the column flow. Signal enhancement is typically 10-50 times for peptides and other small basic molecules. Thus, peptide maps that use ESI-MS for detection can be performed at lower levels, with conventional columns, without the need to use capillary chromatography or reduced mass spectral resolution to achieve satisfactory sensitivity. The method may be used with similar results for heptafluorobutyric acid and hydrochloric acid. A mechanism for TFA signal suppression and signal enhancement by the foregoing method, is proposed.

Performance Analysis of Grey-World-based Feature Detection and Matching for Mobile Positioning Systems

NASA Astrophysics Data System (ADS)

Bejuri, Wan Mohd Yaakob Wan; Mohamad, Mohd Murtadha

2014-11-01

This paper introduces a new grey-world-based feature detection and matching algorithm, intended for use with mobile positioning systems. This approach uses a combination of a wireless local area network (WLAN) and a mobile phone camera to determine positioning in an illumination environment using a practical and pervasive approach. The signal combination is based on retrieved signal strength from the WLAN access point and the image processing information from the building hallways. The results show our method can handle information better than Harlan Hile's method relative to the illumination environment, producing lower illumination error in five (5) different environments.

Distributed Environment Control Using Wireless Sensor/Actuator Networks for Lighting Applications

PubMed Central

Nakamura, Masayuki; Sakurai, Atsushi; Nakamura, Jiro

2009-01-01

We propose a decentralized algorithm to calculate the control signals for lights in wireless sensor/actuator networks. This algorithm uses an appropriate step size in the iterative process used for quickly computing the control signals. We demonstrate the accuracy and efficiency of this approach compared with the penalty method by using Mote-based mesh sensor networks. The estimation error of the new approach is one-eighth as large as that of the penalty method with one-fifth of its computation time. In addition, we describe our sensor/actuator node for distributed lighting control based on the decentralized algorithm and demonstrate its practical efficacy. PMID:22291525

Hierarchical Self Assembly of Patterns from the Robinson Tilings: DNA Tile Design in an Enhanced Tile Assembly Model

PubMed Central

Padilla, Jennifer E.; Liu, Wenyan; Seeman, Nadrian C.

2012-01-01

We introduce a hierarchical self assembly algorithm that produces the quasiperiodic patterns found in the Robinson tilings and suggest a practical implementation of this algorithm using DNA origami tiles. We modify the abstract Tile Assembly Model, (aTAM), to include active signaling and glue activation in response to signals to coordinate the hierarchical assembly of Robinson patterns of arbitrary size from a small set of tiles according to the tile substitution algorithm that generates them. Enabling coordinated hierarchical assembly in the aTAM makes possible the efficient encoding of the recursive process of tile substitution. PMID:23226722

Hierarchical Self Assembly of Patterns from the Robinson Tilings: DNA Tile Design in an Enhanced Tile Assembly Model.

PubMed

Padilla, Jennifer E; Liu, Wenyan; Seeman, Nadrian C

2012-06-01

We introduce a hierarchical self assembly algorithm that produces the quasiperiodic patterns found in the Robinson tilings and suggest a practical implementation of this algorithm using DNA origami tiles. We modify the abstract Tile Assembly Model, (aTAM), to include active signaling and glue activation in response to signals to coordinate the hierarchical assembly of Robinson patterns of arbitrary size from a small set of tiles according to the tile substitution algorithm that generates them. Enabling coordinated hierarchical assembly in the aTAM makes possible the efficient encoding of the recursive process of tile substitution.

A New Signaling Architecture THREP with Autonomous Radio-Link Control for Wireless Communications Systems

NASA Astrophysics Data System (ADS)

Hirono, Masahiko; Nojima, Toshio

This paper presents a new signaling architecture for radio-access control in wireless communications systems. Called THREP (for THREe-phase link set-up Process), it enables systems with low-cost configurations to provide tetherless access and wide-ranging mobility by using autonomous radio-link controls for fast cell searching and distributed call management. A signaling architecture generally consists of a radio-access part and a service-entity-access part. In THREP, the latter part is divided into two steps: preparing a communication channel, and sustaining it. Access control in THREP is thus composed of three separated parts, or protocol phases. The specifications of each phase are determined independently according to system requirements. In the proposed architecture, the first phase uses autonomous radio-link control because we want to construct low-power indoor wireless communications systems. Evaluation of channel usage efficiency and hand-over loss probability in the personal handy-phone system (PHS) shows that THREP makes the radio-access sub-system operations in a practical application model highly efficient, and the results of a field experiment show that THREP provides sufficient protection against severe fast CNR degradation in practical indoor propagation environments.

AIM Photonics: Tomorrow’s Technology at the Speed of Light

DTIC Science & Technology

2016-09-01

design automation companies AIM Photonics Tomorrow’s Technology at the Speed of Light Michael Liehr Defense AT&L: September-October 2010 386...in speed and complexity will increase cost, power consumption and heat too much to allow further, practical miniaturization. Light propagates...Integrated microwave photonic circuits (using light to transmit and process optical signals encoded with ana- log information at frequencies in the

Real Time System for Practical Acoustic Monitoring of Global Ocean Temperature. Volume 3

DTIC Science & Technology

1994-06-30

signal processing software to the SSAR. This software performs Doppler correction , circulating sums, matched filtering and pulse compression, estimation...Doppler correction , circulating sums, matched filtering and pulse compression, estimation of multipath arrival angle, and peak- picking. At the... geometrica , sound speed, and focuing region sAles to the acoustic wavelengths Our work on this problem is based on an oceanographic application. To

Chemiresistive and Gravimetric Dual-Mode Gas Sensor toward Target Recognition and Differentiation.

PubMed

Chen, Yan; Zhang, Hao; Feng, Zhihong; Zhang, Hongxiang; Zhang, Rui; Yu, Yuanyuan; Tao, Jin; Zhao, Hongyuan; Guo, Wenlan; Pang, Wei; Duan, Xuexin; Liu, Jing; Zhang, Daihua

2016-08-24

We demonstrate a dual-mode gas sensor for simultaneous and independent acquisition of electrical and mechanical signals from the same gas adsorption event. The device integrates a graphene field-effect transistor (FET) with a piezoelectric resonator in a seamless manner by leveraging multiple structural and functional synergies. Dual signals resulting from independent physical processes, i.e., mass attachment and charge transfer can reflect intrinsic properties of gas molecules and potentially enable target recognition and quantification at the same time. Fabrication of the device is based on standard Integrated Circuit (IC) foundry processes and fully compatible with system-on-a-chip (SoC) integration to achieve extremely small form factors. In addition, the ability of simultaneous measurements of mass adsorption and charge transfer guides us to a more precise understanding of the interactions between graphene and various gas molecules. Besides its practical functions, the device serves as an effective tool to quantitatively investigate the physical processes and sensing mechanisms for a large library of sensing materials and target analytes.

Modeling Sound Processing in Cochlear Nuclei

NASA Astrophysics Data System (ADS)

Meddis, Ray

2003-03-01

The cochlear nucleus is an obligatory relay nucleus between the ear and the rest of the brain. It consists of many different types of neurons each responding differently to the same stimulus. Much is known about the wiring diagram of the system but it has so far proved difficult to characterise the signal processing that is going on or what purpose it serves. The solution to this problem is a pre-requisite of any attempt to produce a practical electronic simulation that exploits the brain's unique capacity to recognise the significance of acoustic events and generate appropriate responses. This talk will explain the different types of neural cell and specify hypotheses as to their various functions. Cell-types vary in terms of their size and shape as well as the number and type of minute electrical currents that flow across the cell membranes. Computer models will also be used to illustrate how the physical substrate (the wet-ware) is used to achieve its signal-processing goals.

Noise suppression methods for robust speech processing

NASA Astrophysics Data System (ADS)

Boll, S. F.; Ravindra, H.; Randall, G.; Armantrout, R.; Power, R.

1980-05-01

Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during this reporting period for the research program funded to develop real time, compressed speech analysis synthesis algorithms whose performance in invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the current research and results in the areas of noise suppression using the dual input adaptive noise cancellation using the short time Fourier transform algorithms, articulation rate change techniques, and a description of an experiment which demonstrated that the spectral subtraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC 10 coded, helicopter speech by 10.6 point.

From bad pharma to good pharma: aligning market forces with good and trustworthy practices through accreditation, certification, and rating.

PubMed

Miller, Jennifer E

2013-01-01

This article explores whether the bioethical performance and trustworthiness of pharmaceutical companies can be improved by harnessing market forces through the use of accreditation, certification, or rating. Other industries have used such systems to define best practices, set standards, and assess and signal the quality of services, processes, and products. These systems have also informed decisions in other industries about where to invest, what to buy, where to work, and when to regulate. Similarly, accreditation, certification, and rating programs can help drug companies address stakeholder concerns in four areas: clinical trial design and management, dissemination of clinical trial results, marketing practices, and the accessibility of medicines. To illuminate processes - such as conflicts of interests and revolving-door policies - that can jeopardize the integrity of accreditation, certification, and ratings systems, the article concludes with a consideration of recent failures of credit-rating agencies and a review of the regulatory capture literature. © 2013 American Society of Law, Medicine & Ethics, Inc.

Multi-Frequency Signal Detection Based on Frequency Exchange and Re-Scaling Stochastic Resonance and Its Application to Weak Fault Diagnosis

PubMed Central

Leng, Yonggang; Fan, Shengbo

2018-01-01

Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method. PMID:29693577

Assessment of Receiver Signal Strength Sensing for Location Estimation Based on Fisher Information

PubMed Central

Nielsen, John; Nielsen, Christopher

2016-01-01

Currently there is almost ubiquitous availability of wireless signaling for data communications within commercial building complexes resulting in receiver signal strength (RSS) observables that are typically sufficient for generating viable location estimates of mobile wireless devices. However, while RSS observables are generally plentiful, achieving an accurate estimation of location is difficult due to several factors affecting the electromagnetic coupling between the mobile antenna and the building access points that are not modeled and hence contribute to the overall estimation uncertainty. Such uncertainty is typically mitigated with a moderate redundancy of RSS sensor observations in combination with other constraints imposed on the mobile trajectory. In this paper, the Fisher Information (FI) of a set of RSS sensor observations in the context of variables related to the mobile location is developed. This provides a practical method of determining the potential location accuracy for the given set of wireless signals available. Furthermore, the information value of individual RSS measurements can be quantified and the RSS observables weighted accordingly in estimation combining algorithms. The practical utility of using FI in this context was demonstrated experimentally with an extensive set of RSS measurements recorded in an office complex. The resulting deviation of the mobile location estimation based on application of weighted likelihood processing to the experimental RSS data was shown to agree closely with the Cramer Rao bound determined from the FI analysis. PMID:27669262

AUX: a scripting language for auditory signal processing and software packages for psychoacoustic experiments and education.

PubMed

Kwon, Bomjun J

2012-06-01

This article introduces AUX (AUditory syntaX), a scripting syntax specifically designed to describe auditory signals and processing, to the members of the behavioral research community. The syntax is based on descriptive function names and intuitive operators suitable for researchers and students without substantial training in programming, who wish to generate and examine sound signals using a written script. In this article, the essence of AUX is discussed and practical examples of AUX scripts specifying various signals are illustrated. Additionally, two accompanying Windows-based programs and development libraries are described. AUX Viewer is a program that generates, visualizes, and plays sounds specified in AUX. AUX Viewer can also be used for class demonstrations or presentations. Another program, Psycon, allows a wide range of sound signals to be used as stimuli in common psychophysical testing paradigms, such as the adaptive procedure, the method of constant stimuli, and the method of adjustment. AUX Library is also provided, so that researchers can develop their own programs utilizing AUX. The philosophical basis of AUX is to separate signal generation from the user interface needed for experiments. AUX scripts are portable and reusable; they can be shared by other researchers, regardless of differences in actual AUX-based programs, and reused for future experiments. In short, the use of AUX can be potentially beneficial to all members of the research community-both those with programming backgrounds and those without.

Ellipsoidal cell flow system

DOEpatents

Salzman, Gary C.; Mullaney, Paul F.

1976-01-01

The disclosure relates to a system incorporating an ellipsoidal flow chamber having light reflective walls for low level light detection in practicing cellular analysis. The system increases signal-to-noise ratio by a factor of ten over prior art systems. In operation, laser light passes through the primary focus of the ellipsoid. A controlled flow of cells simultaneously passes through this focus so that the laser light impinges on the cells and is modulated by the cells. The reflective walls of the ellipsoid reflect the cell-modulated light to the secondary focus of the ellipsoid. A tapered light guide at the secondary focus picks up a substantial portion of modulated reflective light and directs it onto a light detector to produce a signal. The signal is processed to obtain the intensity distribution of the modulated light and hence sought after characteristics of the cells. In addition, cells may be dyed so as to fluoresce in response to the laser light and their fluorescence may be processed as cell-modulated light above described. A light discriminating filter would be used to distinguish reflected modulated laser light from reflected fluorescent light.

Review of wireless and wearable electroencephalogram systems and brain-computer interfaces--a mini-review.

PubMed

Lin, Chin-Teng; Ko, Li-Wei; Chang, Meng-Hsiu; Duann, Jeng-Ren; Chen, Jing-Ying; Su, Tung-Ping; Jung, Tzyy-Ping

2010-01-01

Biomedical signal monitoring systems have rapidly advanced in recent years, propelled by significant advances in electronic and information technologies. Brain-computer interface (BCI) is one of the important research branches and has become a hot topic in the study of neural engineering, rehabilitation, and brain science. Traditionally, most BCI systems use bulky, wired laboratory-oriented sensing equipments to measure brain activity under well-controlled conditions within a confined space. Using bulky sensing equipments not only is uncomfortable and inconvenient for users, but also impedes their ability to perform routine tasks in daily operational environments. Furthermore, owing to large data volumes, signal processing of BCI systems is often performed off-line using high-end personal computers, hindering the applications of BCI in real-world environments. To be practical for routine use by unconstrained, freely-moving users, BCI systems must be noninvasive, nonintrusive, lightweight and capable of online signal processing. This work reviews recent online BCI systems, focusing especially on wearable, wireless and real-time systems. Copyright 2009 S. Karger AG, Basel.

Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

PubMed Central

Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

2018-01-01

Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

20 kHz toluene planar laser-induced fluorescence imaging of a jet in nearly sonic crossflow

NASA Astrophysics Data System (ADS)

Miller, V. A.; Troutman, V. A.; Mungal, M. G.; Hanson, R. K.

2014-10-01

This manuscript describes continuous, high-repetition-rate (20 kHz) toluene planar laser-induced fluorescence (PLIF) imaging in an expansion tube impulse flow facility. Cinematographic image sequences are acquired that visualize an underexpanded jet of hydrogen in Mach 0.9 crossflow, a practical flow configuration relevant to aerospace propulsion systems. The freestream gas is nitrogen seeded with toluene; toluene broadly absorbs and fluoresces in the ultraviolet, and the relatively high quantum yield of toluene produces large signals and high signal-to-noise ratios. Toluene is excited using a commercially available, frequency-quadrupled (266 nm), high-repetition-rate (20 kHz), pulsed (0.8-0.9 mJ per pulse), diode-pumped solid-state Nd:YAG laser, and fluorescence is imaged with a high-repetition-rate intensifier and CMOS camera. The resulting PLIF movie and image sequences are presented, visualizing the jet start-up process and the dynamics of the jet in crossflow; the freestream duration and a measure of freestream momentum flux steadiness are also inferred. This work demonstrates progress toward continuous PLIF imaging of practical flow systems in impulse facilities at kHz acquisition rates using practical, turn-key, high-speed laser and imaging systems.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Controlled ion track etching

NASA Astrophysics Data System (ADS)

George, J.; Irkens, M.; Neumann, S.; Scherer, U. W.; Srivastava, A.; Sinha, D.; Fink, D.

2006-03-01

It is a common practice since long to follow the ion track-etching process in thin foils via conductometry, i.e . by measurement of the electrical current which passes through the etched track, once the track breakthrough condition has been achieved. The major disadvantage of this approach, namely the absence of any major detectable signal before breakthrough, can be avoided by examining the track-etching process capacitively. This method allows one to define precisely not only the breakthrough point before it is reached, but also the length of any non-transient track. Combining both capacitive and conductive etching allows one to control the etching process perfectly. Examples and possible applications are given.

Vascular Sap Proteomics: Providing Insight into Long-Distance Signaling during Stress

PubMed Central

Carella, Philip; Wilson, Daniel C.; Kempthorne, Christine J.; Cameron, Robin K.

2016-01-01

The plant vascular system, composed of the xylem and phloem, is important for the transport of water, mineral nutrients, and photosynthate throughout the plant body. The vasculature is also the primary means by which developmental and stress signals move from one organ to another. Due to practical and technological limitations, proteomics analysis of xylem and phloem sap has been understudied in comparison to accessible sample types such as leaves and roots. However, recent advances in sample collection techniques and mass spectrometry technology are making it possible to comprehensively analyze vascular sap proteomes. In this mini-review, we discuss the emerging field of vascular sap proteomics, with a focus on recent comparative studies to identify vascular proteins that may play roles in long-distance signaling and other processes during stress responses in plants. PMID:27242852

[INVITED] Signal and noise in Laser Induced Breakdown Spectroscopy: An introductory review

NASA Astrophysics Data System (ADS)

Tognoni, Elisabetta; Cristoforetti, Gabriele

2016-05-01

Laser Induced Breakdown Spectroscopy (LIBS) has become a very popular technique for elemental analysis thanks to its ease of use. However, LIBS users often report poor repeatability of the signal, due to shot-to-shot fluctuations, and consequent not satisfactory limits of detection. In many practical cases, these shortcomings are difficult to control because the signal is affected by several noise sources that cannot be reduced simultaneously. Hopefully, there is a large amount of knowledge, accumulated during several decades, that can provide guidelines to reduce the effect of the single sources of fluctuations. Experimental setup and measurement settings can be optimized on purpose. Spectral data can be processed in order to better exploit the information contained. In the current paper several approaches to improve the analytical figures-of-merit are reviewed and the respective advantages and drawbacks are discussed.

Channel Modeling

NASA Astrophysics Data System (ADS)

Schmitz, Arne; Schinnenburg, Marc; Gross, James; Aguiar, Ana

For any communication system the Signal-to-Interference-plus-Noise-Ratio of the link is a fundamental metric. Recall (cf. Chapter 9) that the SINR is defined as the ratio between the received power of the signal of interest and the sum of all "disturbing" power sources (i.e. interference and noise). From information theory it is known that a higher SINR increases the maximum possible error-free transmission rate (referred to as Shannon capacity [417] of any communication system and vice versa). Conversely, the higher the SINR, the lower will be the bit error rate in practical systems. While one aspect of the SINR is the sum of all distracting power sources, another issue is the received power. This depends on the transmitted power, the used antennas, possibly on signal processing techniques and ultimately on the channel gain between transmitter and receiver.

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

PubMed

Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and mitigation of PLP.

An Anticipatory Model of Cavitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, G.O.; Dress, W.B., Jr.; Hylton, J.O.

1999-04-05

The Anticipatory System (AS) formalism developed by Robert Rosen provides some insight into the problem of embedding intelligent behavior in machines. AS emulates the anticipatory behavior of biological systems. AS bases its behavior on its expectations about the near future and those expectations are modified as the system gains experience. The expectation is based on an internal model that is drawn from an appeal to physical reality. To be adaptive, the model must be able to update itself. To be practical, the model must run faster than real-time. The need for a physical model and the requirement that the modelmore » execute at extreme speeds, has held back the application of AS to practical problems. Two recent advances make it possible to consider the use of AS for practical intelligent sensors. First, advances in transducer technology make it possible to obtain previously unavailable data from which a model can be derived. For example, acoustic emissions (AE) can be fed into a Bayesian system identifier that enables the separation of a weak characterizing signal, such as the signature of pump cavitation precursors, from a strong masking signal, such as a pump vibration feature. The second advance is the development of extremely fast, but inexpensive, digital signal processing hardware on which it is possible to run an adaptive Bayesian-derived model faster than real-time. This paper reports the investigation of an AS using a model of cavitation based on hydrodynamic principles and Bayesian analysis of data from high-performance AE sensors.« less

p-exponent and p-leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Leonarduzzi, R.; Wendt, H.; Abry, P.; Jaffard, S.; Melot, C.; Roux, S. G.; Torres, M. E.

2016-04-01

Multifractal analysis studies signals, functions, images or fields via the fluctuations of their local regularity along time or space, which capture crucial features of their temporal/spatial dynamics. It has become a standard signal and image processing tool and is commonly used in numerous applications of different natures. In its common formulation, it relies on the Hölder exponent as a measure of local regularity, which is by nature restricted to positive values and can hence be used for locally bounded functions only. In this contribution, it is proposed to replace the Hölder exponent with a collection of novel exponents for measuring local regularity, the p-exponents. One of the major virtues of p-exponents is that they can potentially take negative values. The corresponding wavelet-based multiscale quantities, the p-leaders, are constructed and shown to permit the definition of a new multifractal formalism, yielding an accurate practical estimation of the multifractal properties of real-world data. Moreover, theoretical and practical connections to and comparisons against another multifractal formalism, referred to as multifractal detrended fluctuation analysis, are achieved. The performance of the proposed p-leader multifractal formalism is studied and compared to previous formalisms using synthetic multifractal signals and images, illustrating its theoretical and practical benefits. The present contribution is complemented by a companion article studying in depth the theoretical properties of p-exponents and the rich classification of local singularities it permits.

Implementation of Bluetooth technology in processing aspheric mirrors

NASA Astrophysics Data System (ADS)

Chen, Dong-yun; Li, Xiao-jin

2010-10-01

This paper adopts the Bluetooth wireless transmission to replace the conducting rings currently using in the active lap process to overcome the cost and abrasion problems brought by the conducting rings, which has great significance for reducing the costs of processing large aspheric mirrors. Based on the actual application requirements, Article proposes the overall program of using Bluetooth technology as data transmission, including the active lap-side and machine tool-side: In the machine tool-side, the MCU separately connects with Bluetooth module and the sensor via UART0 and UART1 serial port, and when the MCU receives the signals sending from the sensor, the MCU packs and then sends them through the Bluetooth module; while in the active lap side, the CCAL reads-out the position signals of sensor detecting in dual-port memory via one-side ports, and the other side ports connect with the MCU's high ports P4-P7, so the MCU can unpacks and stores the position signals receiving via Bluetooth module. This paper designs and implements the system's hardware circuit, and mainly introduces the ways of serial and parallel. Based upon the realized system, design the test program for the Bluetooth wireless transmission and the experiment results, in the condition of the active lap processing large aspheric mirrors, showed that Bluetooth technology can meet the requirements of practical applications.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

On adaptive robustness approach to Anti-Jam signal processing

NASA Astrophysics Data System (ADS)

Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

A compact semiconductor digital interferometer and its applications

NASA Astrophysics Data System (ADS)

Britsky, Oleksander I.; Gorbov, Ivan V.; Petrov, Viacheslav V.; Balagura, Iryna V.

2015-05-01

The possibility of using semiconductor laser interferometers to measure displacements at the nanometer scale was demonstrated. The creation principles of miniature digital Michelson interferometers based on semiconductor lasers were proposed. The advanced processing algorithm for the interferometer quadrature signals was designed. It enabled to reduce restrictions on speed of measured movements. A miniature semiconductor digital Michelson interferometer was developed. Designing of the precision temperature stability system for miniature low-cost semiconductor laser with 0.01ºС accuracy enabled to use it for creation of compact interferometer rather than a helium-neon one. Proper firmware and software was designed for the interferometer signals real-time processing and conversion in to respective shifts. In the result the relative displacement between 0-500 mm was measured with a resolution of better than 1 nm. Advantages and disadvantages of practical use of the compact semiconductor digital interferometer in seismometers for the measurement of shifts were shown.

A method for reduction of Acoustic Emission (AE) data with application in machine failure detection and diagnosis

NASA Astrophysics Data System (ADS)

Vicuña, Cristián Molina; Höweler, Christoph

2017-12-01

The use of AE in machine failure diagnosis has increased over the last years. Most AE-based failure diagnosis strategies use digital signal processing and thus require the sampling of AE signals. High sampling rates are required for this purpose (e.g. 2 MHz or higher), leading to streams of large amounts of data. This situation is aggravated if fine resolution and/or multiple sensors are required. These facts combine to produce bulky data, typically in the range of GBytes, for which sufficient storage space and efficient signal processing algorithms are required. This situation probably explains why, in practice, AE-based methods consist mostly in the calculation of scalar quantities such as RMS and Kurtosis, and the analysis of their evolution in time. While the scalar-based approach offers the advantage of maximum data reduction; it has the disadvantage that most part of the information contained in the raw AE signal is lost unrecoverably. This work presents a method offering large data reduction, while keeping the most important information conveyed by the raw AE signal, useful for failure detection and diagnosis. The proposed method consist in the construction of a synthetic, unevenly sampled signal which envelopes the AE bursts present on the raw AE signal in a triangular shape. The constructed signal - which we call TriSignal - also permits the estimation of most scalar quantities typically used for failure detection. But more importantly, it contains the information of the time of occurrence of the bursts, which is key for failure diagnosis. Lomb-Scargle normalized periodogram is used to construct the TriSignal spectrum, which reveals the frequency content of the TriSignal and provides the same information as the classic AE envelope. The paper includes application examples in planetary gearbox and low-speed rolling element bearing.

Optical amplifiers for coherent lidar

NASA Technical Reports Server (NTRS)

Fork, Richard

1996-01-01

We examine application of optical amplification to coherent lidar for the case of a weak return signal (a number of quanta of the return optical field close to unity). We consider the option that has been explored to date, namely, incorporation of an optical amplifier operated in a linear manner located after reception of the signal and immediately prior to heterodyning and photodetection. We also consider alternative strategies where the coherent interaction, the nonlinear processes, and the amplification are not necessarily constrained to occur in the manner investigated to date. We include the complications that occur because of mechanisms that occur at the level of a few, or one, quantum excitation. Two factors combine in the work to date that limit the value of the approach. These are: (1) the weak signal tends to require operation of the amplifier in the linear regime where the important advantages of nonlinear optical processing are not accessed, (2) the linear optical amplifier has a -3dB noise figure (SN(out)/SN(in)) that necessarily degrades the signal. Some improvement is gained because the gain provided by the optical amplifier can be used to overcome losses in the heterodyned process and photodetection. The result, however, is that introduction of an optical amplifier in a well optimized coherent lidar system results in, at best, a modest improvement in signal to noise. Some improvement may also be realized on incorporating more optical components in a coherent lidar system for purely practical reasons. For example, more compact, lighter weight, components, more robust alignment, or more rapid processing may be gained. We further find that there remain a number of potentially valuable, but unexplored options offered both by the rapidly expanding base of optical technology and the recent investigation of novel nonlinear coherent interference phenomena occurring at the single quantum excitation level. Key findings are: (1) insertion of linear optical amplifiers in well optimized conventional lidar systems offers modest improvements, at best, (2) the practical advantages of optical amplifiers, especially fiber amplifiers, such as ease of alignment, compactness, efficiency, lightweight, etc., warrant further investigation for coherent lidar, (3) the possibility of more fully optical lidar systems should be explored, (4) advantages gained by use of coherent interference of optical fields at the level of one, or a few, signal quanta should be explored, (5) amplification without inversion, population trapping, and use of electromagnetic induced transparency warrant investigation in connection with coherent lidar, (6) these new findings are probably more applicable to earth related NASA work, although applications to deep space should not be excluded, and (7) our own work in the Ultrafast Laboratory at UAH along some of the above lines of investigation, may be useful.

Research on signal processing of shock absorber test bench based on zero-phase filter

NASA Astrophysics Data System (ADS)

Wu, Yi; Ding, Guoqing

2017-10-01

The quality of force-displacement diagram is significant to help evaluate the performance of shock absorbers. Damping force sampling data is often interfered by Gauss white noise, 50Hz power interference and its harmonic wave during the process of testing; data de-noising has become the core problem of drawing true, accurate and real-time indicator diagram. The noise and interference can be filtered out through generic IIR or FIR low-pass filter, but addition phase lag of useful signal will be caused due to the inherent attribute of IIR and FIR filter. The paper uses FRR method to realize zero-phase digital filtering in a software way based on mutual cancellation of phase lag between the forward and reverse sequences after through the filter. High-frequency interference above 40Hz are filtered out completely and noise attenuation is more than -40dB, with no additional phase lag. The method is able to restore the true signal as far as possible. Theoretical simulation and practical test indicate high-frequency noises have been effectively inhibited in multiple typical speed cases, signal-to-noise ratio being greatly improved; the curve in indicator diagram has better smoothness and fidelity. The FRR algorithm has low computational complexity, fast running time, and can be easily transplanted in multiple platforms.

Coherent detection in optical fiber systems.

PubMed

Ip, Ezra; Lau, Alan Pak Tao; Barros, Daniel J F; Kahn, Joseph M

2008-01-21

The drive for higher performance in optical fiber systems has renewed interest in coherent detection. We review detection methods, including noncoherent, differentially coherent, and coherent detection, as well as a hybrid method. We compare modulation methods encoding information in various degrees of freedom (DOF). Polarization-multiplexed quadrature-amplitude modulation maximizes spectral efficiency and power efficiency, by utilizing all four available DOF, the two field quadratures in the two polarizations. Dual-polarization homodyne or heterodyne downconversion are linear processes that can fully recover the received signal field in these four DOF. When downconverted signals are sampled at the Nyquist rate, compensation of transmission impairments can be performed using digital signal processing (DSP). Linear impairments, including chromatic dispersion and polarization-mode dispersion, can be compensated quasi-exactly using finite impulse response filters. Some nonlinear impairments, such as intra-channel four-wave mixing and nonlinear phase noise, can be compensated partially. Carrier phase recovery can be performed using feedforward methods, even when phase-locked loops may fail due to delay constraints. DSP-based compensation enables a receiver to adapt to time-varying impairments, and facilitates use of advanced forward-error-correction codes. We discuss both single- and multi-carrier system implementations. For a given modulation format, using coherent detection, they offer fundamentally the same spectral efficiency and power efficiency, but may differ in practice, because of different impairments and implementation details. With anticipated advances in analog-to-digital converters and integrated circuit technology, DSP-based coherent receivers at bit rates up to 100 Gbit/s should become practical within the next few years.

Are individuals with higher psychopathic traits better learners at lying? Behavioural and neural evidence.

PubMed

Shao, R; Lee, T M C

2017-07-25

High psychopathy is characterized by untruthfulness and manipulativeness. However, existing evidence on higher propensity or capacity to lie among non-incarcerated high-psychopathic individuals is equivocal. Of particular importance, no research has investigated whether greater psychopathic tendency is associated with better 'trainability' of lying. An understanding of whether the neurobehavioral processes of lying are modifiable through practice offers significant theoretical and practical implications. By employing a longitudinal design involving university students with varying degrees of psychopathic traits, we successfully demonstrate that the performance speed of lying about face familiarity significantly improved following two sessions of practice, which occurred only among those with higher, but not lower, levels of psychopathic traits. Furthermore, this behavioural improvement associated with higher psychopathic tendency was predicted by a reduction in lying-related neural signals and by functional connectivity changes in the frontoparietal and cerebellum networks. Our findings provide novel and pivotal evidence suggesting that psychopathic traits are the key modulating factors of the plasticity of both behavioural and neural processes underpinning lying. These findings broadly support conceptualization of high-functioning individuals with higher psychopathic traits as having preserved, or arguably superior, functioning in neural networks implicated in cognitive executive processing, but deficiencies in affective neural processes, from a neuroplasticity perspective.

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

PubMed Central

Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D

2004-01-01

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598

BCI2000: a general-purpose brain-computer interface (BCI) system.

PubMed

Schalk, Gerwin; McFarland, Dennis J; Hinterberger, Thilo; Birbaumer, Niels; Wolpaw, Jonathan R

2004-06-01

Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.

Characteristics and limitations of GPS L1 observations from submerged antennas - Theoretical investigation in snow, ice, and freshwater and practical observations within a freshwater layer

NASA Astrophysics Data System (ADS)

Steiner, Ladina; Meindl, Michael; Geiger, Alain

2018-05-01

Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.

Change in physiological signals during mindfulness meditation

PubMed Central

Ahani, Asieh; Wahbeh, Helane; Miller, Meghan; Nezamfar, Hooman; Erdogmus, Deniz; Oken, Barry

2014-01-01

Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods. PMID:24748422

Design of the intelligent smoke alarm system based on photoelectric smoke

NASA Astrophysics Data System (ADS)

Ma, Jiangfei; Yang, Xiufang; Wang, Peipei

2017-02-01

This paper designed a kind of intelligent smoke alarm system based on photoelectric smoke detector and temperature, The system takes AT89C51 MCU as the core of hardware control and Labview as the host computer monitoring center.The sensor system acquires temperature signals and smoke signals, the MCU control A/D by Sampling and converting the output analog signals , and then the two signals will be uploaded to the host computer through the serial communication. To achieve real-time monitoring of smoke and temperature in the environment, LabVIEW monitoring platform need to hold, process, analysis and display these samping signals. The intelligent smoke alarm system is suitable for large scale shopping malls and other public places, which can greatly reduce the false alarm rate of fire, The experimental results show that the system runs well and can alarm when the setting threshold is reached,and the threshold parameters can be adjusted according to the actual conditions of the field. The system is easy to operate, simple in structure, intelligent, low cost, and with strong practical value.

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

NASA Astrophysics Data System (ADS)

Dong, Shaojiang; Sun, Dihua; Xu, Xiangyang; Tang, Baoping

2017-06-01

Aiming at the problem that it is difficult to extract the feature information from the space bearing vibration signal because of different noise, for example the running trend information, high-frequency noise and especially the existence of lot of power line interference (50Hz) and its octave ingredients of the running space simulated equipment in the ground. This article proposed a combination method to eliminate them. Firstly, the EMD is used to remove the running trend item information of the signal, the running trend that affect the signal processing accuracy is eliminated. Then the morphological filter is used to eliminate high-frequency noise. Finally, the components and characteristics of the power line interference are researched, based on the characteristics of the interference, the revised blind source separation model is used to remove the power line interferences. Through analysis of simulation and practical application, results suggest that the proposed method can effectively eliminate those noise.

Fringe pattern information retrieval using wavelets

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Patimo, Caterina; Manicone, Pasquale D.; Lamberti, Luciano

2005-08-01

Two-dimensional phase modulation is currently the basic model used in the interpretation of fringe patterns that contain displacement information, moire, holographic interferometry, speckle techniques. Another way to look to these two-dimensional signals is to consider them as frequency modulated signals. This alternative interpretation has practical implications similar to those that exist in radio engineering for handling frequency modulated signals. Utilizing this model it is possible to obtain frequency information by using the energy approach introduced by Ville in 1944. A natural complementary tool of this process is the wavelet methodology. The use of wavelet makes it possible to obtain the local values of the frequency in a one or two dimensional domain without the need of previous phase retrieval and differentiation. Furthermore from the properties of wavelets it is also possible to obtain at the same time the phase of the signal with the advantage of a better noise removal capabilities and the possibility of developing simpler algorithms for phase unwrapping due to the availability of the derivative of the phase.

Reconstruction of pulse noisy images via stochastic resonance

PubMed Central

Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

2015-01-01

We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

Studying Cellular Signal Transduction with OMIC Technologies.

PubMed

Landry, Benjamin D; Clarke, David C; Lee, Michael J

2015-10-23

In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly non-linear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases, signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

The influence of digital filter type, amplitude normalisation method, and co-contraction algorithm on clinically relevant surface electromyography data during clinical movement assessments.

PubMed

Devaprakash, Daniel; Weir, Gillian J; Dunne, James J; Alderson, Jacqueline A; Donnelly, Cyril J

2016-12-01

There is a large and growing body of surface electromyography (sEMG) research using laboratory-specific signal processing procedures (i.e., digital filter type and amplitude normalisation protocols) and data analyses methods (i.e., co-contraction algorithms) to acquire practically meaningful information from these data. As a result, the ability to compare sEMG results between studies is, and continues to be challenging. The aim of this study was to determine if digital filter type, amplitude normalisation method, and co-contraction algorithm could influence the practical or clinical interpretation of processed sEMG data. Sixteen elite female athletes were recruited. During data collection, sEMG data was recorded from nine lower limb muscles while completing a series of calibration and clinical movement assessment trials (running and sidestepping). Three analyses were conducted: (1) signal processing with two different digital filter types (Butterworth or critically damped), (2) three amplitude normalisation methods, and (3) three co-contraction ratio algorithms. Results showed the choice of digital filter did not influence the clinical interpretation of sEMG; however, choice of amplitude normalisation method and co-contraction algorithm did influence the clinical interpretation of the running and sidestepping task. Care is recommended when choosing amplitude normalisation method and co-contraction algorithms if researchers/clinicians are interested in comparing sEMG data between studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Microwave life detector for buried victims using neutrodyning loop based system

NASA Astrophysics Data System (ADS)

Tahar J., Bel Hadj

2009-07-01

This paper describes a new design of an electromagnetic life detector for the detection of buried victims. The principle of the microwave life sensor is based on the detection of the modulated part of a scattered wave which is generated by the breathing activity of the victim. Those movements generate a spectral component located in the low frequency range, which for most of the cases, is located in a spectrum extending from 0.18 Hz to 0.34 Hz. The detection process requires high sensitivity with respect to breathing movements and, simultaneously, a relative insensitivity for other non-modulated or modulated parasitic signals. Developed microwave system, generating a frequency adjustable between 500 MHz and 1 GHz, is based on a neutrodyning loop required to cancel any non-modulated background and reflected signals in order to get better receiver sensitivity without introducing supplementary distortions on the received signal. Life signal is considered practically periodic that facilitates the extraction of this spectral component using several processing techniques, such as adaptive filtering and correlation permitting to ameliorate the detection range to be more than 15 m in low-loss medium. Detection range is a fundamental parameter for a microwave life detector. A range around 1 m doesn't have a large interest for this application. To attain a range more than 15 m, while guaranteeing professional performances, the technology has to optimize the system parameters as well as the involved signal processing for the purpose of overcoming the presence of obstacles, attenuation, and noise perturbation. This constitutes the main contribution of the present work. Experimental measurements have confirmed the potentiality of this microwave technique for life detector with best space covering detection.

Online Denoising Based on the Second-Order Adaptive Statistics Model.

PubMed

Yi, Sheng-Lun; Jin, Xue-Bo; Su, Ting-Li; Tang, Zhen-Yun; Wang, Fa-Fa; Xiang, Na; Kong, Jian-Lei

2017-07-20

Online denoising is motivated by real-time applications in the industrial process, where the data must be utilizable soon after it is collected. Since the noise in practical process is usually colored, it is quite a challenge for denoising techniques. In this paper, a novel online denoising method was proposed to achieve the processing of the practical measurement data with colored noise, and the characteristics of the colored noise were considered in the dynamic model via an adaptive parameter. The proposed method consists of two parts within a closed loop: the first one is to estimate the system state based on the second-order adaptive statistics model and the other is to update the adaptive parameter in the model using the Yule-Walker algorithm. Specifically, the state estimation process was implemented via the Kalman filter in a recursive way, and the online purpose was therefore attained. Experimental data in a reinforced concrete structure test was used to verify the effectiveness of the proposed method. Results show the proposed method not only dealt with the signals with colored noise, but also achieved a tradeoff between efficiency and accuracy.

The technology on noise reduction of the APD detection circuit

NASA Astrophysics Data System (ADS)

Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong

2013-09-01

The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.

Optimization of chlorine fluxing process for magnesium removal from molten aluminum

NASA Astrophysics Data System (ADS)

Fu, Qian

High-throughput and low operational cost are the keys to a successful industrial process. Much aluminum is now recycled in the form of used beverage cans and this aluminum is of alloys that contain high levels of magnesium. It is common practice to "demag" the metal by injecting chlorine that preferentially reacts with the magnesium. In the conventional chlorine fluxing processes, low reaction efficiency results in excessive reactive gas emissions. In this study, through an experimental investigation of the reaction kinetics involved in this process, a mathematical model is set up for the purpose of process optimization. A feedback controlled chlorine reduction process strategy is suggested for demagging the molten aluminum to the desired magnesium level without significant gas emissions. This strategy also needs the least modification of the existing process facility. The suggested process time will only be slightly longer than conventional methods and chlorine usage and emissions will be reduced. In order to achieve process optimization through novel designs in any fluxing process, a system is necessary for measuring the bubble distribution in liquid metals. An electro-resistivity probe described in the literature has low accuracy and its capability to measure bubble distribution has not yet been fully demonstrated. A capacitance bubble probe was designed for bubble measurements in molten metals. The probe signal was collected and processed digitally. Higher accuracy was obtained by higher discrimination against corrupted signals. A single-size bubble experiment in Belmont metal was designed to reveal the characteristic response of the capacitance probe. This characteristic response fits well with a theoretical model. It is suggested that using a properly designed deconvolution process, the actual bubble size distribution can be calculated. The capacitance probe was used to study some practical bubble generation devices. Preliminary results on bubble distribution generated by a porous plug in Belmont metal showed bubbles much bigger than those in a water model. Preliminary results in molten aluminum showed that the probe was applicable in this harsh environment. An interesting bubble coalescence phenomenon was also observed in both Belmont metal and molten aluminum.

Method for measuring the alternating current half-wave voltage of a Mach-Zehnder modulator based on opto-electronic oscillation.

PubMed

Hong, Jun; Chen, Dongchu; Peng, Zhiqiang; Li, Zulin; Liu, Haibo; Guo, Jian

2018-05-01

A new method for measuring the alternating current (AC) half-wave voltage of a Mach-Zehnder modulator is proposed and verified by experiment in this paper. Based on the opto-electronic self-oscillation technology, the physical relationship between the saturation output power of the oscillating signal and the AC half-wave voltage is revealed, and the value of the AC half-wave voltage is solved by measuring the saturation output power of the oscillating signal. The experimental results show that the measured data of this new method involved are in agreement with a traditional method, and not only an external microwave signal source but also the calibration for different frequency measurements is not needed in our new method. The measuring process is simplified with this new method on the premise of ensuring the accuracy of measurement, and it owns good practical value.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Implication of high dynamic range and wide color gamut content distribution

NASA Astrophysics Data System (ADS)

Lu, Taoran; Pu, Fangjun; Yin, Peng; Chen, Tao; Husak, Walt

2015-09-01

High Dynamic Range (HDR) and Wider Color Gamut (WCG) content represents a greater range of luminance levels and a more complete reproduction of colors found in real-world scenes. The current video distribution environments deliver Standard Dynamic Range (SDR) signal. Therefore, there might be some significant implication on today's end-to-end ecosystem from content creation to distribution and finally to consumption. For SDR content, the common practice is to apply compression on Y'CbCr 4:2:0 using gamma transfer function and non-constant luminance 4:2:0 chroma subsampling. For HDR and WCG content, it is desirable to examine if such signal format still works well for compression, and it is interesting to know if the overall system performance can be further improved by exploring different signal formats and processing workflows. In this paper, we will provide some of our insight into those problems.

An all digital low data rate communication system

NASA Technical Reports Server (NTRS)

Chen, C.; Fan, M.

1973-01-01

The advent of digital hardwares has made it feasible to implement many communication system components digitally. With the exception of frequency down conversion, the proposed low data rate communication system uses digital hardwares completely. Although the system is designed primarily for deep space communications with large frequency uncertainty and low signal-to-noise ratio, it is also suitable for other low data rate applications with time-shared operation among a number of channels. Emphasis is placed on the fast Fourier transform receiver and the automatic frequency control via digital filtering. The speed available from the digital system allows sophisticated signal processing to reduce frequency uncertainty and to increase the signal-to-noise ratio. The practical limitations of the system such as the finite register length are examined. It is concluded that the proposed all-digital system is not only technically feasible but also has potential cost reduction over the existing receiving systems.

Laser Welding Process Monitoring Systems: Advanced Signal Analysis for Quality Assurance

NASA Astrophysics Data System (ADS)

D'Angelo, Giuseppe

Laser material processing today is widely used in industry. Especially laser welding became one of the key-technologies, e. g., for the automotive sector. This is due to the improvement and development of new laser sources and the increasing knowledge gained at countless scientific research projects. Nevertheless, it is still not possible to use the full potential of this technology. Therefore, the introduction and application of quality-assuring systems is required. For a long time, the statement "the best sensor is no sensor" was often heard. Today, a change of paradigm can be observed. On the one hand, ISO 9000 and other by law enforced regulations have led to the understanding that quality monitoring is an essential tool in modern manufacturing and necessary in order to keep production results in deterministic boundaries. On the other hand, rising quality requirements not only set higher and higher requirements for the process technology but also demand qualityassurance measures which ensure the reliable recognition of process faults. As a result, there is a need for reliable online detection and correction of welding faults by means of an in-process monitoring. The chapter describes an advanced signals analysis technique to extract information from signals detected, during the laser welding process, by optical sensors. The technique is based on the method of reassignment which was first applied to the spectrogram by Kodera, Gendrin and de Villedary22,23 and later generalized to any bilinear time-frequency representation by Auger and Flandrin.24 Key to the method is a nonlinear convolution where the value of the convolution is not placed at the center of the convolution kernel but rather reassigned to the center of mass of the function within the kernel. The resulting reassigned representation yields significantly improved components localization. We compare the proposed time-frequency distributions by analyzing signals detected during the laser welding of tailored blanks, demonstrating the advantages of the reassigned representation, giving practical applicability to the proposed method.

Cyclic Nucleotide Phosphodiesterases: important signaling modulators and therapeutic targets

PubMed Central

Ahmad, Faiyaz; Murata, Taku; Simizu, Kasumi; Degerman, Eva; Maurice, Donald; Manganiello, Vincent

2014-01-01

By catalyzing hydrolysis of cAMP and cGMP, cyclic nucleotide phosphodiesterases are critical regulators of their intracellular concentrations and their biological effects. Since these intracellular second messengers control many cellular homeostatic processes, dysregulation of their signals and signaling pathways initiate or modulate pathophysiological pathways related to various disease states, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication, chronic obstructive pulmonary disease, and psoriasis. Alterations in expression of PDEs and PDE-gene mutations (especially mutations in PDE6, PDE8B, PDE11A and PDE4) have been implicated in various diseases and cancer pathologies. PDEs also play important role in formation and function of multi-molecular signaling/regulatory complexes called signalosomes. At specific intracellular locations, individual PDEs, together with pathway-specific signaling molecules, regulators, and effectors, are incorporated into specific signalosomes, where they facilitate and regulate compartmentalization of cyclic nucleotide signaling pathways and specific cellular functions. Currently, only a limited number of PDE inhibitors (PDE3, PDE4, PDE5 inhibitors) are used in clinical practice. Future paths to novel drug discovery include the crystal structure-based design approach, which has resulted in generation of more effective family-selective inhibitors, as well as burgeoning development of strategies to alter compartmentalized cyclic nucleotide signaling pathways by selectively targeting individual PDEs and their signalosome partners. PMID:25056711

Biosensors with Built-In Biomolecular Logic Gates for Practical Applications

PubMed Central

Lai, Yu-Hsuan; Sun, Sin-Cih; Chuang, Min-Chieh

2014-01-01

Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems. PMID:25587423

Evaluation of arterial stiffness by finger-toe pulse wave velocity: optimization of signal processing and clinical validation.

PubMed

Obeid, Hasan; Khettab, Hakim; Marais, Louise; Hallab, Magid; Laurent, Stéphane; Boutouyrie, Pierre

2017-08-01

Carotid-femoral pulse wave velocity (PWV) (cf-PWV) is the gold standard for measuring aortic stiffness. Finger-toe PWV (ft-PWV) is a simpler noninvasive method for measuring arterial stiffness. Although the validity of the method has been previously assessed, its accuracy can be improved. ft-PWV is determined on the basis of a patented height chart for the distance and the pulse transit time (PTT) between the finger and the toe pulpar arteries signals (ft-PTT). The objective of the first study, performed in 66 patients, was to compare different algorithms (intersecting tangents, maximum of the second derivative, 10% threshold and cross-correlation) for determining the foot of the arterial pulse wave, thus the ft-PTT. The objective of the second study, performed in 101 patients, was to investigate different signal processing chains to improve the concordance of ft-PWV with the gold-standard cf-PWV. Finger-toe PWV (ft-PWV) was calculated using the four algorithms. The best correlations relating ft-PWV and cf-PWV, and relating ft-PTT and carotid-femoral PTT were obtained with the maximum of the second derivative algorithm [PWV: r = 0.56, P < 0.0001, root mean square error (RMSE) = 0.9 m/s; PTT: r = 0.61, P < 0.001, RMSE = 12 ms]. The three other algorithms showed lower correlations. The correlation between ft-PTT and carotid-femoral PTT further improved (r = 0.81, P < 0.0001, RMSE = 5.4 ms) when the maximum of the second derivative algorithm was combined with an optimized signal processing chain. Selecting the maximum of the second derivative algorithm for detecting the foot of the pressure waveform, and combining it with an optimized signal processing chain, improved the accuracy of ft-PWV measurement in the current population sample. Thus, it makes ft-PWV very promising for the simple noninvasive determination of aortic stiffness in clinical practice.

Analysis of swept-sine runs during modal identification

NASA Astrophysics Data System (ADS)

Gloth, G.; Sinapius, M.

2004-11-01

Experimental modal analysis of large aerospace structures in Europe combine nowadays the benefits of the very reliable but time-consuming phase resonance method and the application of phase separation techniques evaluating frequency response functions (FRF). FRFs of a test structure can be determined by a variety of means. Applied excitation signal waveforms include harmonic signals like stepped-sine excitation, periodic signals like multi-sine excitation, transient signals like impulse and swept-sine excitation, and stochastic signals like random. The current article focuses on slow swept-sine excitation which is a good trade-off between magnitude of excitation level needed for large aircraft and testing time. However, recent ground vibration tests (GVTs) brought up that reliable modal data from swept-sine test runs depend on a proper data processing. The article elucidates the strategy of modal analysis based on swept-sine excitation. The standards for the application of slowly swept sinusoids defined by the international organisation for standardisation in ISO 7626 part 2 are critically reviewed. The theoretical background of swept-sine testing is expounded with particular emphasis to the transition through structural resonances. The effect of different standard procedures of data processing like tracking filter, fast Fourier transform (FFT), and data reduction via averaging are investigated with respect to their influence on the FRFs and modal parameters. Particular emphasis is given to FRF distortions evoked by unsuitable data processing. All data processing methods are investigated on a numerical example. Their practical usefulness is demonstrated on test data taken from a recent GVT on a large aircraft. The revision of ISO 7626 part 2 is suggested regarding the application of slow swept-sine excitation. Recommendations about the proper FRF estimation from slow swept-sine excitation are given in order to enable the optimisation on these applications for future modal survey tests of large aerospace structures.

A Volterra series-based method for extracting target echoes in the seafloor mining environment.

PubMed

Zhao, Haiming; Ji, Yaqian; Hong, Yujiu; Hao, Qi; Ma, Liyong

2016-09-01

The purpose of this research was to evaluate the applicability of the Volterra adaptive method to predict the target echo of an ultrasonic signal in an underwater seafloor mining environment. There is growing interest in mining of seafloor minerals because they offer an alternative source of rare metals. Mining the minerals cause the seafloor sediments to be stirred up and suspended in sea water. In such an environment, the target signals used for seafloor mapping are unable to be detected because of the unavoidable presence of volume reverberation induced by the suspended sediments. The detection of target signals in reverberation is currently performed using a stochastic model (for example, the autoregressive (AR) model) based on the statistical characterisation of reverberation. However, we examined a new method of signal detection in volume reverberation based on the Volterra series by confirming that the reverberation is a chaotic signal and generated by a deterministic process. The advantage of this method over the stochastic model is that attributions of the specific physical process are considered in the signal detection problem. To test the Volterra series based method and its applicability to target signal detection in the volume reverberation environment derived from the seafloor mining process, we simulated the real-life conditions of seafloor mining in a water filled tank of dimensions of 5×3×1.8m. The bottom of the tank was covered with 10cm of an irregular sand layer under which 5cm of an irregular cobalt-rich crusts layer was placed. The bottom was interrogated by an acoustic wave generated as 16μs pulses of 500kHz frequency. This frequency is demonstrated to ensure a resolution on the order of one centimetre, which is adequate in exploration practice. Echo signals were collected with a data acquisition card (PCI 1714 UL, 12-bit). Detection of the target echo in these signals was performed by both the Volterra series based model and the AR model. The results obtained confirm that the Volterra series based method is more efficient in the detection of the signal in reverberation than the conventional AR model (the accuracy is 80% for the PIM-Volterra prediction model versus 40% for the AR model). Copyright © 2016 Elsevier B.V. All rights reserved.

Role of biomolecular logic systems in biosensors and bioactuators

NASA Astrophysics Data System (ADS)

Mailloux, Shay; Katz, Evgeny

2014-09-01

An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

Interoception, contemplative practice, and health

PubMed Central

Farb, Norman; Daubenmier, Jennifer; Price, Cynthia J.; Gard, Tim; Kerr, Catherine; Dunn, Barnaby D.; Klein, Anne Carolyn; Paulus, Martin P.; Mehling, Wolf E.

2015-01-01

Interoception can be broadly defined as the sense of signals originating within the body. As such, interoception is critical for our sense of embodiment, motivation, and well-being. And yet, despite its importance, interoception remains poorly understood within modern science. This paper reviews interdisciplinary perspectives on interoception, with the goal of presenting a unified perspective from diverse fields such as neuroscience, clinical practice, and contemplative studies. It is hoped that this integrative effort will advance our understanding of how interoception determines well-being, and identify the central challenges to such understanding. To this end, we introduce an expanded taxonomy of interoceptive processes, arguing that many of these processes can be understood through an emerging predictive coding model for mind–body integration. The model, which describes the tension between expected and felt body sensation, parallels contemplative theories, and implicates interoception in a variety of affective and psychosomatic disorders. We conclude that maladaptive construal of bodily sensations may lie at the heart of many contemporary maladies, and that contemplative practices may attenuate these interpretative biases, restoring a person’s sense of presence and agency in the world. PMID:26106345

Titanium dioxide nanowire sensor array integration on CMOS platform using deterministic assembly.

PubMed

Gall, Oren Z; Zhong, Xiahua; Schulman, Daniel S; Kang, Myungkoo; Razavieh, Ali; Mayer, Theresa S

2017-06-30

Nanosensor arrays have recently received significant attention due to their utility in a wide range of applications, including gas sensing, fuel cells, internet of things, and portable health monitoring systems. Less attention has been given to the production of sensor platforms in the μW range for ultra-low power applications. Here, we discuss how to scale the nanosensor energy demand by developing a process for integration of nanowire sensing arrays on a monolithic CMOS chip. This work demonstrates an off-chip nanowire fabrication method; subsequently nanowires link to a fused SiO 2 substrate using electric-field assisted directed assembly. The nanowire resistances shown in this work have the highest resistance uniformity reported to date of 18%, which enables a practical roadmap towards the coupling of nanosensors to CMOS circuits and signal processing systems. The article also presents the utility of optimizing annealing conditions of the off-chip metal-oxides prior to CMOS integration to avoid limitations of thermal budget and process incompatibility. In the context of the platform demonstrated here, directed assembly is a powerful tool that can realize highly uniform, cross-reactive arrays of different types of metal-oxide nanosensors suited for gas discrimination and signal processing systems.

Titanium dioxide nanowire sensor array integration on CMOS platform using deterministic assembly

NASA Astrophysics Data System (ADS)

Gall, Oren Z.; Zhong, Xiahua; Schulman, Daniel S.; Kang, Myungkoo; Razavieh, Ali; Mayer, Theresa S.

2017-06-01

Nanosensor arrays have recently received significant attention due to their utility in a wide range of applications, including gas sensing, fuel cells, internet of things, and portable health monitoring systems. Less attention has been given to the production of sensor platforms in the μW range for ultra-low power applications. Here, we discuss how to scale the nanosensor energy demand by developing a process for integration of nanowire sensing arrays on a monolithic CMOS chip. This work demonstrates an off-chip nanowire fabrication method; subsequently nanowires link to a fused SiO2 substrate using electric-field assisted directed assembly. The nanowire resistances shown in this work have the highest resistance uniformity reported to date of 18%, which enables a practical roadmap towards the coupling of nanosensors to CMOS circuits and signal processing systems. The article also presents the utility of optimizing annealing conditions of the off-chip metal-oxides prior to CMOS integration to avoid limitations of thermal budget and process incompatibility. In the context of the platform demonstrated here, directed assembly is a powerful tool that can realize highly uniform, cross-reactive arrays of different types of metal-oxide nanosensors suited for gas discrimination and signal processing systems.

UV-visible-DAD and 1H-NMR spectroscopy data fusion for studying the photodegradation process of azo-dyes using MCR-ALS.

PubMed

Fernández, Cristina; Pilar Callao, M; Larrechi, M Soledad

2013-12-15

The photodegradation process of three azo-dyes - Acid Orange 61, Acid Red 97 and Acid Brown 425 - was monitored simultaneously by ultraviolet-visible spectroscopy with diode array detector (UV-vis-DAD) and (1)H-nuclear magnetic resonance ((1)H-NMR). Multivariate curve resolution-alternating least squares (MCR-ALS) was applied to obtain the concentration and spectral profile of the chemical compounds involved in the process. The analysis of the H-NMR data suggests there are more intermediate compounds than those obtained with the UV-vis-DAD data. The fusion of UV-vis-DAD and the (1)H-NMR signal before the multivariate analysis provides better results than when only one of the two detector signals was used. It was concluded that three degradation products were present in the medium when the three azo-dyes had practically degraded. This study is the first application of UV-vis-DAD and (1)H-NMR spectroscopy data fusion in this field and illustrates its potential as a quick method for evaluating the evolution of the azo-dye photodegradation process. © 2013 Elsevier B.V. All rights reserved.

A fuzzy decision tree for fault classification.

PubMed

Zio, Enrico; Baraldi, Piero; Popescu, Irina C

2008-02-01

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

PubMed

Mobli, Mehdi; Hoch, Jeffrey C

2014-11-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language: Computational techniques are presented to analyze and model expressed and perceived human behavior-variedly characterized as typical, atypical, distressed, and disordered-from speech and language cues and their applications in health, commerce, education, and beyond.

PubMed

Narayanan, Shrikanth; Georgiou, Panayiotis G

2013-02-07

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion.

A nanoforest structure for practical surface-enhanced Raman scattering substrates

NASA Astrophysics Data System (ADS)

Seol, Myeong-Lok; Choi, Sung-Jin; Baek, David J.; Park, Tae Jung; Ahn, Jae-Hyuk; Lee, Sang Yup; Choi, Yang-Kyu

2012-03-01

A nanoforest structure for surface-enhanced Raman scattering (SERS) active substrates is fabricated and analyzed. The detailed morphology of the resulting structure can be easily controlled by modifying the process parameters such as initial gold layer thickness and etching time. The applicability of the nanoforest substrate as a label-free SERS immunosensor is demonstrated using influenza A virus subtype H1N1. Selective binding of the H1N1 surface antigen and the anti-H1 antibody is directly detected by the SERS signal differences. Simple fabrication and high throughput with strong in-plane hot-spots imply that the nanoforest structure can be a practical sensing component of a chip-based SERS sensing system.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

White Gaussian Noise - Models for Engineers

NASA Astrophysics Data System (ADS)

Jondral, Friedrich K.

2018-04-01

This paper assembles some information about white Gaussian noise (WGN) and its applications. It starts from a description of thermal noise, i. e. the irregular motion of free charge carriers in electronic devices. In a second step, mathematical models of WGN processes and their most important parameters, especially autocorrelation functions and power spectrum densities, are introduced. In order to proceed from mathematical models to simulations, we discuss the generation of normally distributed random numbers. The signal-to-noise ratio as the most important quality measure used in communications, control or measurement technology is accurately introduced. As a practical application of WGN, the transmission of quadrature amplitude modulated (QAM) signals over additive WGN channels together with the optimum maximum likelihood (ML) detector is considered in a demonstrative and intuitive way.

A decision-directed network for dual-polarization crosstalk cancellation

NASA Technical Reports Server (NTRS)

Weber, W. J., III

1979-01-01

Frequency reuse in the specific form of dual-polarized microwave communication systems has grown in importance in recent years as a practical means of radio spectrum conservation. Ideally the capacity of a given frequency allocation can be doubled through dual-polarization. However, hardware imperfections and propagation effects, particularly rain depolarization, prevent the achievement of this doubling without severe system performance degradation. A decision-directed cross-polarization correction network is presented whose operation depends on only simple base-band signal processing. No pilot tones or frequency offsets are required. The loop can work with any two-dimensional signal set for digital data transmission. The loop has been experimentally verified and provides a means of doubling the data capacity with little performance degradation.

A Framework for Modeling Competitive and Cooperative Computation in Retinal Processing

NASA Astrophysics Data System (ADS)

Moreno-Díaz, Roberto; de Blasio, Gabriel; Moreno-Díaz, Arminda

2008-07-01

The structure of the retina suggests that it should be treated (at least from the computational point of view), as a layered computer. Different retinal cells contribute to the coding of the signals down to ganglion cells. Also, because of the nature of the specialization of some ganglion cells, the structure suggests that all these specialization processes should take place at the inner plexiform layer and they should be of a local character, prior to a global integration and frequency-spike coding by the ganglion cells. The framework we propose consists of a layered computational structure, where outer layers provide essentially with band-pass space-time filtered signals which are progressively delayed, at least for their formal treatment. Specialization is supposed to take place at the inner plexiform layer by the action of spatio-temporal microkernels (acting very locally), and having a centerperiphery space-time structure. The resulting signals are then integrated by the ganglion cells through macrokernels structures. Practically all types of specialization found in different vertebrate retinas, as well as the quasilinear behavior in some higher vertebrates, can be modeled and simulated within this framework. Finally, possible feedback from central structures is considered. Though their relevance to retinal processing is not definitive, it is included here for the sake of completeness, since it is a formal requisite for recursiveness.

Relating memory to functional performance in normal aging to dementia using hierarchical Bayesian cognitive processing models.

PubMed

Shankle, William R; Pooley, James P; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D

2013-01-01

Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.

Speech transport for packet telephony and voice over IP

NASA Astrophysics Data System (ADS)

Baker, Maurice R.

1999-11-01

Recent advances in packet switching, internetworking, and digital signal processing technologies have converged to allow realizable practical implementations of packet telephony systems. This paper provides a tutorial on transmission engineering for packet telephony covering the topics of speech coding/decoding, speech packetization, packet data network transport, and impairments which may negatively impact end-to-end system quality. Particular emphasis is placed upon Voice over Internet Protocol given the current popularity and ubiquity of IP transport.

SPECT detectors: the Anger Camera and beyond

PubMed Central

Peterson, Todd E.; Furenlid, Lars R.

2011-01-01

The development of radiation detectors capable of delivering spatial information about gamma-ray interactions was one of the key enabling technologies for nuclear medicine imaging and, eventually, single-photon emission computed tomography (SPECT). The continuous NaI(Tl) scintillator crystal coupled to an array of photomultiplier tubes, almost universally referred to as the Anger Camera after its inventor, has long been the dominant SPECT detector system. Nevertheless, many alternative materials and configurations have been investigated over the years. Technological advances as well as the emerging importance of specialized applications, such as cardiac and preclinical imaging, have spurred innovation such that alternatives to the Anger Camera are now part of commercial imaging systems. Increased computing power has made it practical to apply advanced signal processing and estimation schemes to make better use of the information contained in the detector signals. In this review we discuss the key performance properties of SPECT detectors and survey developments in both scintillator and semiconductor detectors and their readouts with an eye toward some of the practical issues at least in part responsible for the continuing prevalence of the Anger Camera in the clinic. PMID:21828904

Theory of Remote Image Formation

NASA Astrophysics Data System (ADS)

Blahut, Richard E.

2004-11-01

In many applications, images, such as ultrasonic or X-ray signals, are recorded and then analyzed with digital or optical processors in order to extract information. Such processing requires the development of algorithms of great precision and sophistication. This book presents a unified treatment of the mathematical methods that underpin the various algorithms used in remote image formation. The author begins with a review of transform and filter theory. He then discusses two- and three-dimensional Fourier transform theory, the ambiguity function, image construction and reconstruction, tomography, baseband surveillance systems, and passive systems (where the signal source might be an earthquake or a galaxy). Information-theoretic methods in image formation are also covered, as are phase errors and phase noise. Throughout the book, practical applications illustrate theoretical concepts, and there are many homework problems. The book is aimed at graduate students of electrical engineering and computer science, and practitioners in industry. Presents a unified treatment of the mathematical methods that underpin the algorithms used in remote image formation Illustrates theoretical concepts with reference to practical applications Provides insights into the design parameters of real systems

A Wavelet Model for Vocalic Speech Coarticulation

DTIC Science & Technology

1994-10-01

control vowel’s signal as the mother wavelet. A practical experiment is conducted to evaluate the coarticulation channel using samples 01 real speech...transformation from a control speech state (input) to an effected speech state (output). Specifically, a vowel produced in isolation is transformed into an...the wavelet transform of the effected vowel’s signal, using the control vowel’s signal as the mother wavelet. A practical experiment is conducted to

The magnetic fields generated by the tsunami of February 27, 2010

NASA Astrophysics Data System (ADS)

Nair, M. C.; Maus, S.; Neetu, S.; Kuvshinov, A. V.; Chulliat, A.

2010-12-01

It has long been speculated that tsunamis produce measurable perturbations in the magnetic field. Recent deployments of highly accurate magnetometers and the exceptionally deep solar minimum provided ideal conditions to identify these small signals for the tsunami resulting from the strong Chilean earthquake on February 27, 2010. We find that the magnetic observatory measurements on Easter Island, 3500 km west of the epicenter, show a periodic signal of 1 nT, coincident in time with recordings from the local tide gauge. The amplitude of this signal is consistent with the sea level variation caused by the tsunami in the open ocean near Easter Island through a scaling method proposed by Tyler (2005). In order to have a better understanding of this process, we predict the magnetic fields induced by the Chile tsunami using a barotropic-shallow-water model along with a three-dimensional electromagnetic induction code (Kuvshinov et al., 2002). Initial results indicate good agreement between the predicted and observed magnetic signals at Easter Island. The detection of these magnetic signals represents a milestone in understanding tsunami-induced electromagnetic effects. However, magnetospheric disturbances could limit the practical utility of tsunami electromagnetic monitoring to periods of low solar activity.

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

A cell-phone-based brain-computer interface for communication in daily life

NASA Astrophysics Data System (ADS)

Wang, Yu-Te; Wang, Yijun; Jung, Tzyy-Ping

2011-04-01

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

Detecting Disease in Radiographs with Intuitive Confidence

PubMed Central

2015-01-01

This paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values are directly related with the two forces Yin and Yang. The angle for which sine and cosine are equal (45°) represents the state of equilibrium between Yin and Yang, which is a state of nonduality that indicates neither normality nor abnormality in terms of disease classification. The paper claims that the proposed confidence is intuitive and can be readily understood by physicians. The paper underpins this thesis with theoretical results in neural signal processing, stating that a sine/cosine relationship between the actual input signal and the perceived (learned) input is key to neural learning processes. As a practical example, the paper shows how to use the proposed confidence values to highlight manifestations of tuberculosis in frontal chest X-rays. PMID:26495433

A cell-phone-based brain-computer interface for communication in daily life.

PubMed

Wang, Yu-Te; Wang, Yijun; Jung, Tzyy-Ping

2011-04-01

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

A High-Temperature Piezoresistive Pressure Sensor with an Integrated Signal-Conditioning Circuit.

PubMed

Yao, Zong; Liang, Ting; Jia, Pinggang; Hong, Yingping; Qi, Lei; Lei, Cheng; Zhang, Bin; Xiong, Jijun

2016-06-18

This paper focuses on the design and fabrication of a high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit, which consists of an encapsulated pressure-sensitive chip, a temperature compensation circuit and a signal-conditioning circuit. A silicon on insulation (SOI) material and a standard MEMS process are used in the pressure-sensitive chip fabrication, and high-temperature electronic components are adopted in the temperature-compensation and signal-conditioning circuits. The entire pressure sensor achieves a hermetic seal and can be operated long-term in the range of -50 °C to 220 °C. Unlike traditional pressure sensor output voltage ranges (in the dozens to hundreds of millivolts), the output voltage of this sensor is from 0 V to 5 V, which can significantly improve the signal-to-noise ratio and measurement accuracy in practical applications of long-term transmission based on experimental verification. Furthermore, because this flexible sensor's output voltage is adjustable, general follow-up pressure transmitter devices for voltage converters need not be used, which greatly reduces the cost of the test system. Thus, the proposed high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit is expected to be highly applicable to pressure measurements in harsh environments.

A High-Temperature Piezoresistive Pressure Sensor with an Integrated Signal-Conditioning Circuit

PubMed Central

Yao, Zong; Liang, Ting; Jia, Pinggang; Hong, Yingping; Qi, Lei; Lei, Cheng; Zhang, Bin; Xiong, Jijun

2016-01-01

This paper focuses on the design and fabrication of a high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit, which consists of an encapsulated pressure-sensitive chip, a temperature compensation circuit and a signal-conditioning circuit. A silicon on insulation (SOI) material and a standard MEMS process are used in the pressure-sensitive chip fabrication, and high-temperature electronic components are adopted in the temperature-compensation and signal-conditioning circuits. The entire pressure sensor achieves a hermetic seal and can be operated long-term in the range of −50 °C to 220 °C. Unlike traditional pressure sensor output voltage ranges (in the dozens to hundreds of millivolts), the output voltage of this sensor is from 0 V to 5 V, which can significantly improve the signal-to-noise ratio and measurement accuracy in practical applications of long-term transmission based on experimental verification. Furthermore, because this flexible sensor’s output voltage is adjustable, general follow-up pressure transmitter devices for voltage converters need not be used, which greatly reduces the cost of the test system. Thus, the proposed high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit is expected to be highly applicable to pressure measurements in harsh environments. PMID:27322288

A digital boxcar integrator for IMS spectra

NASA Technical Reports Server (NTRS)

Cohen, Martin J.; Stimac, Robert M.; Wernlund, Roger F.; Parker, Donald C.

1995-01-01

When trying to detect or quantify a signal at or near the limit of detectability, it is invariably embeded in the noise. This statement is true for nearly all detectors of any physical phenomena and the limit of detectability, hopefully, occurs at very low signal-to-noise levels. This is particularly true of IMS (Ion Mobility Spectrometers) spectra due to the low vapor pressure of several chemical compounds of great interest and the small currents associated with the ionic detection process. Gated Integrators and Boxcar Integrators or Averagers are designed to recover fast, repetitive analog signals. In a typical application, a time 'Gate' or 'Window' is generated, characterized by a set delay from a trigger or gate pulse and a certain width. A Gated Integrator amplifies and integrates the signal that is present during the time the gate is open, ignoring noise and interference that may be present at other times. Boxcar Integration refers to the practice of averaging the output of the Gated Integrator over many sweeps of the detector. Since any signal present during the gate will add linearly, while noise will add in a 'random walk' fashion as the square root of the number of sweeps, averaging N sweeps will improve the 'Signal-to-Noise Ratio' by a factor of the square root of N.

Unidirectional signal propagation in primary neurons micropatterned at a single-cell resolution

NASA Astrophysics Data System (ADS)

Yamamoto, H.; Matsumura, R.; Takaoki, H.; Katsurabayashi, S.; Hirano-Iwata, A.; Niwano, M.

2016-07-01

The structure and connectivity of cultured neuronal networks can be controlled by using micropatterned surfaces. Here, we demonstrate that the direction of signal propagation can be precisely controlled at a single-cell resolution by growing primary neurons on micropatterns. To achieve this, we first examined the process by which axons develop and how synapses form in micropatterned primary neurons using immunocytochemistry. By aligning asymmetric micropatterns with a marginal gap, it was possible to pattern primary neurons with a directed polarization axis at the single-cell level. We then examined how synapses develop on micropatterned hippocampal neurons. Three types of micropatterns with different numbers of short paths for dendrite growth were compared. A normal development in synapse density was observed when micropatterns with three or more short paths were used. Finally, we performed double patch clamp recordings on micropatterned neurons to confirm that these synapses are indeed functional, and that the neuronal signal is transmitted unidirectionally in the intended orientation. This work provides a practical guideline for patterning single neurons to design functional neuronal networks in vitro with the direction of signal propagation being controlled.

Development of a portable Linux-based ECG measurement and monitoring system.

PubMed

Tan, Tan-Hsu; Chang, Ching-Su; Huang, Yung-Fa; Chen, Yung-Fu; Lee, Cheng

2011-08-01

This work presents a portable Linux-based electrocardiogram (ECG) signals measurement and monitoring system. The proposed system consists of an ECG front end and an embedded Linux platform (ELP). The ECG front end digitizes 12-lead ECG signals acquired from electrodes and then delivers them to the ELP via a universal serial bus (USB) interface for storage, signal processing, and graphic display. The proposed system can be installed anywhere (e.g., offices, homes, healthcare centers and ambulances) to allow people to self-monitor their health conditions at any time. The proposed system also enables remote diagnosis via Internet. Additionally, the system has a 7-in. interactive TFT-LCD touch screen that enables users to execute various functions, such as scaling a single-lead or multiple-lead ECG waveforms. The effectiveness of the proposed system was verified by using a commercial 12-lead ECG signal simulator and in vivo experiments. In addition to its portability, the proposed system is license-free as Linux, an open-source code, is utilized during software development. The cost-effectiveness of the system significantly enhances its practical application for personal healthcare.

Driver performance modelling and its practical application to railway safety.

PubMed

Hamilton, W Ian; Clarke, Theresa

2005-11-01

This paper reports on the development and main features of a model of driver information processing. The work was conducted on behalf of Network Rail to meet a requirement to understand and manage the driver's interaction with the infrastructure through lineside reminder appliances. The model utilises cognitive theory and modelling techniques to describe driver performance in relation to infrastructure features and operational conditions. The model is capable of predicting the performance time, workload and error consequences of different operational conditions. The utility of the model is demonstrated through reports of its application to the following studies: Research on the effect of line speed on driver interaction with signals and signs. Calculation of minimum reading times for signals. Development of a human factors signals passed at danger (SPAD) hazard checklist, and a method to resolve conflicts between signal sighting solutions. Research on the demands imposed on drivers by European train control system (ETCS) driving in a UK context. The paper also reports on a validation of the model's utility as a tool for assessing cab and infrastructure drivability.

FastICA peel-off for ECG interference removal from surface EMG.

PubMed

Chen, Maoqi; Zhang, Xu; Chen, Xiang; Zhu, Mingxing; Li, Guanglin; Zhou, Ping

2016-06-13

Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference. It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference. The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.

Nurses' care practices at the end of life in intensive care units in Bahrain.

PubMed

O'Neill, Catherine S; Yaqoob, Maryam; Faraj, Sumaya; O'Neill, Carla L

2017-12-01

The process of dying in intensive care units is complex as the technological environment shapes clinical decisions. Decisions at the end of life require the involvement of patient, families and healthcare professionals. The degree of involvement can vary depending on the professional and social culture of the unit. Nurses have an important role to play in caring for dying patients and their families; however, their knowledge is not always sought. This study explored nurses' care practices at the end of life, with the objective of describing and identifying end of life care practices that nurses contribute to, with an emphasis on culture, religious experiences and professional identity. Research Design and context: Grounded theory was used. In all, 10 nurses from intensive care unit in two large hospitals in Bahrain were participated. Ethical Considerations: Approval to carry out the research was given by the Research Ethics Committee of the host institution, and the two hospitals. A core category, Death Avoidance Talk, was emerged. This was supported by two major categories: (1) order-oriented care and (2) signalling death and care shifting. Death talk was avoided by the nurses, doctors and family members. When a decision was made by the medical team that a patient was not to be resuscitated, the nurses took this as a sign that death was imminent. This led to a process of signalling death to family and of shifting care to family members. Despite the avoidance of death talk and nurses' lack of professional autonomy, they created awareness that death was imminent to family members and ensured that end of life care was given in a culturally sensitive manner and aligned to Islamic values.

A Practice-Oriented Bifurcation Analysis for Pulse Energy Converters. Part 2: An Operating Regime

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

The paper continues the discussion on bifurcation analysis for applications in practice-oriented solutions for pulse energy conversion systems (PEC-systems). Since a PEC-system represents a nonlinear object with a variable structure, then the description of its dynamics evolution involves bifurcation analysis conceptions. This means the necessity to resolve the conflict-of-units between the notions used to describe natural evolution (i.e. evolution of the operating process towards nonoperating processes and vice versa) and the notions used to describe a desirable artificial regime (i.e. an operating regime). We consider cause-effect relations in the following sequence: nonlinear dynamics-output signal-operating characteristics, where these characteristics include stability and performance. Then regularities of nonlinear dynamics should be translated into regularities of the output signal dynamics, and, after, into an evolutional picture of each operating characteristic. In order to make the translation without losses, we first take into account heterogeneous properties within the structures of the operating process in the parametrical (P-) and phase (X-) spaces, and analyze regularities of the operating stability and performance on the common basis by use of the modified bifurcation diagrams built in joint PX-space. Then, the correspondence between causes (degradation of the operating process stability) and effects (changes of the operating characteristics) is decomposed into three groups of abnormalities: conditionally unavoidable abnormalities (CU-abnormalities); conditionally probable abnormalities (CP-abnormalities); conditionally regular abnormalities (CR-abnormalities). Within each of these groups the evolutional homogeneity is retained. After, the resultant evolution of each operating characteristic is naturally aggregated through the superposition of cause-effect relations in accordance with each of the abnormalities. We demonstrate that the practice-oriented bifurcation analysis has fundamentally specific purposes and tools, like for the computer-based bifurcation analysis and the experimental bifurcation analysis. That is why, from our viewpoint, it seems to be a rather novel direction in the general context of bifurcation analysis conceptions. We believe that the discussion could be interesting to pioneer research intended for the design of promising systems of pulse energy conversion.

Signal and noise level estimation for narrow spectral width returns observed by the Indian MST radar

NASA Astrophysics Data System (ADS)

Hooper, D. A.

1999-07-01

Use is made of five sets of multibeam observations of the lower atmosphere made by the Indian mesosphere-stratosphere-troposphere (MST) radar. Two aspects of signal processing which can lead to serious underestimates of the signal-to-noise ratio are considered. First, a comparison is made of the effects of different data weighting windows applied to the inphase and quadrature components of the radar return samples prior to Fourier transformation. The relatively high degree of spectral leakage associated with the rectangular and Hamming windows can give rise to overestimates of the noise levels by up to 28 dB for the strongest signals. Use of the Hanning window is found to be the most appropriate for these particular data. Second, a technique for removing systematic dc biases from the data in the time domain is compared with the more well-known practice of correction in the frequency domain. The latter technique, which is often used to remove the effects of ground clutter, is shown to be particularly inappropriate for the characteristically narrow spectral width signals observed by the Indian MST radar. For cases of near-zero Doppler shift it can remove up to 30 dB of signal information. The consequences of noise and signal level discrepancies for studies of refractivity structures are discussed. It is shown that neither problem has a significant effect on Doppler shift or spectral width estimates.

Gun muzzle flash detection using a single photon avalanche diode array in 0.18µm CMOS technology

NASA Astrophysics Data System (ADS)

Savuskan, Vitali; Jakobson, Claudio; Merhav, Tomer; Shoham, Avi; Brouk, Igor; Nemirovsky, Yael

2015-05-01

In this study, a CMOS Single Photon Avalanche Diode (SPAD) 2D array is used to record and sample muzzle flash events in the visible spectrum, from representative weapons. SPADs detect the emission peaks of alkali salts, potassium or sodium, with spectral emission lines around 769nm and 589nm, respectively. The alkali salts are included in the gunpowder to suppress secondary flashes ignited during the muzzle flash event. The SPADs possess two crucial properties for muzzle flash imaging: (i) very high photon detection sensitivity, (ii) a unique ability to convert the optical signal to a digital signal at the source pixel, thus practically eliminating readout noise. The sole noise sources are the ones prior to the readout circuitry (optical signal distribution, avalanche initiation distribution and nonphotonic generation). This enables high sampling frequencies in the kilohertz range without significant SNR degradation, in contrast to regular CMOS image sensors. This research will demonstrate the SPAD's ability to accurately sample and reconstruct the temporal behavior of the muzzle flash in the visible wavelength, in the presence of sunlight. The reconstructed signal is clearly distinguishable from background clutter, through exploitation of flash temporal characteristics and signal processing, which will be reported. The frame rate of ~16 KHz was chosen as an optimum between SNR degradation and temporal profile recognition accuracy. In contrast to a single SPAD, the 2D array allows for multiple events to be processed simultaneously. Moreover, a significant field of view is covered, enabling comprehensive surveillance and imaging.

Perceptual learning for speech in noise after application of binary time-frequency masks

PubMed Central

Ahmadi, Mahnaz; Gross, Vauna L.; Sinex, Donal G.

2013-01-01

Ideal time-frequency (TF) masks can reject noise and improve the recognition of speech-noise mixtures. An ideal TF mask is constructed with prior knowledge of the target speech signal. The intelligibility of a processed speech-noise mixture depends upon the threshold criterion used to define the TF mask. The study reported here assessed the effect of training on the recognition of speech in noise after processing by ideal TF masks that did not restore perfect speech intelligibility. Two groups of listeners with normal hearing listened to speech-noise mixtures processed by TF masks calculated with different threshold criteria. For each group, a threshold criterion that initially produced word recognition scores between 0.56–0.69 was chosen for training. Listeners practiced with one set of TF-masked sentences until their word recognition performance approached asymptote. Perceptual learning was quantified by comparing word-recognition scores in the first and last training sessions. Word recognition scores improved with practice for all listeners with the greatest improvement observed for the same materials used in training. PMID:23464038

49 CFR 218.23 - Blue signal display.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Blue signal display. 218.23 Section 218.23..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.23 Blue signal display. (a) Blue signals displayed in accordance with § 218.25, 218.27, or 218.29 signify that...

49 CFR 218.23 - Blue signal display.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Blue signal display. 218.23 Section 218.23..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.23 Blue signal display. (a) Blue signals displayed in accordance with § 218.25, 218.27, or 218.29 signify that...

49 CFR 218.23 - Blue signal display.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Blue signal display. 218.23 Section 218.23..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.23 Blue signal display. (a) Blue signals displayed in accordance with § 218.25, 218.27, or 218.29 signify that...

49 CFR 218.23 - Blue signal display.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Blue signal display. 218.23 Section 218.23..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.23 Blue signal display. (a) Blue signals displayed in accordance with § 218.25, 218.27, or 218.29 signify that...

49 CFR 218.23 - Blue signal display.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Blue signal display. 218.23 Section 218.23..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.23 Blue signal display. (a) Blue signals displayed in accordance with § 218.25, 218.27, or 218.29 signify that...

On the Spectrum of Periodic Signals

ERIC Educational Resources Information Center

Al-Smadi, Adnan

2004-01-01

In theory, there are many methods for the representation of signals. In practice, however, Fourier analysis involving the resolution of signals into sinusoidal components is used widely. There are several methods for Fourier analysis available for representation of signals. If the signal is periodic, then the Fourier series is used to represent…

The detection of T-wave variation linked to arrhythmic risk: an industry perspective.

PubMed

Xue, Joel; Rowlandson, Ian

2013-01-01

Although the scientific literature contains ample descriptions of peculiar patterns of repolarization linked to arrhythmic risk, the objective quantification and classification of these patterns continues to be a challenge that impacts their widespread adoption in clinical practice. To advance the science, computerized algorithms spawned in the academic environment have been essential in order to find, extract and measure these patterns. However, outside the strict control of a core lab, these algorithms are exposed to poor quality signals and need to be effective in the presence of different forms of noise that can either obscure or mimic the T-wave variation (TWV) of interest. To provide a practical solution that can be verified and validated for the market, important tradeoffs need to be made that are based on an intimate understanding of the end-user as well as the key characteristics of either the signal or the noise that can be used by the signal processing engineer to best differentiate them. To illustrate this, two contemporary medical devices used for quantifying T-wave variation are presented, including the modified moving average (MMA) for the detection of T-wave Alternans (TWA) and the quantification of T-wave shape as inputs to the Morphology Combination Score (MCS) for the trending of drug-induced repolarization abnormalities. © 2013 Elsevier Inc. All rights reserved.

Behaviour of Electron Content in the Ionospheric D-Region During Solar X-Ray Flares

NASA Astrophysics Data System (ADS)

Todorović Drakul, M.; Čadež, V. M.; Bajčetić, J.; Popović, L. Č.; Blagojević, D.; Nina, A.

2016-12-01

One of the most important parameters in ionospheric plasma research, also having a wide practical application in wireless satellite telecommunications, is the total electron content (TEC) representing the columnal electron number density. The F-region with high electron density provides the biggest contribution to TEC while the relatively weakly ionized plasma of the D-region (60 km - 90 km above Earth's surface) is often considered as a negligible cause of satellite signal disturbances. However, sudden intensive ionization processes, like those induced by solar X-ray flares, can cause relative increases of electron density that are significantly larger in the D-region than in regions at higher altitudes. Therefore, one cannot exclude a priori the D-region from investigations of ionospheric influences on propagation of electromagnetic signals emitted by satellites. We discuss here this problem which has not been sufficiently treated in literature so far. The obtained results are based on data collected from the D-region monitoring by very low frequency radio waves and on vertical TEC calculations from the Global Navigation Satellite System (GNSS) signal analyses, and they show noticeable variations in the D-region's electron content (TEC_{D) during activity of a solar X-ray flare (it rises by a factor of 136 in the considered case) when TEC_{D} contribution to TEC can reach several percent and which cannot be neglected in practical applications like global positioning procedures by satellites.

Electromagnetic spectrum management system

DOEpatents

Seastrand, Douglas R.

2017-01-31

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process the unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.

Optical fiber sensors for life support applications

NASA Technical Reports Server (NTRS)

Lieberman, R. A.; Schmidlin, E. M.; Ferrell, D. J.; Syracuse, S. J.

1992-01-01

Preliminary experimental results on systems designed to demonstrate sensor operation in regenerative food production and crew air supply applications are presented. The systems use conventional fibers and sources in conjunction with custom wavelength division multiplexers in their optical signal processing sections and nonstandard porous optical fibers in the optical sensing elements. It is considered to be possible to create practical sensors for life-support system applications, and particularly, in regenerative food production environments, based on based on reversible sensors for oxygen, carbon monoxide, and humidity.

Photoactivation of Akt1/GSK3β Isoform-Specific Signaling Axis Promotes Pancreatic β-Cell Regeneration.

PubMed

Huang, Lei; Jiang, Xiaoxiao; Gong, Longlong; Xing, Da

2015-08-01

Promotion of insulin-secreting β-cell regeneration in patients with diabetes is a promising approach for diabetes therapy, which can contribute to rescue the uncontrolled hyperglycemia. Low-power laser irradiation (LPLI) has been demonstrated to regulate multiple physiological processes both in vitro and in vivo through activation of various signaling pathways. In the present study, we showed that LPLI promoted β-cell replication and cell cycle progression through activation of Akt1/GSK3β isoform-specific signaling axis. Inhibition of PI3-K/Akt or GSK3 with specific inhibitors dramatically reduced or increased LPLI-induced β-cell replication, revealing Akt/GSK3 signaling axis was involved in β-cell replication and survival upon LPLI treatment. Furthermore, the results of shRNA-mediated knock down of Akt/GSK3 isoforms revealed that Akt1/GSK3β isoform-specific signaling axis regulated β-cell replication and survival in response to LPLI, but not Akt2/GSK3α. The mechanism by which LPLI promoted β-cell replication through Akt1/GSK3β signaling axis involved activation of β-catenin and down-regulation of p21. Taken together, these observations suggest that Akt1/GSK3β isoform signaling axis play a key role in β-cell replication and survival induced by LPLI. Moreover, our findings suggest that activation of Akt1/GSK3β isoform signaling axis by LPLI may provide guidance in practical applications for β-cell regenerative therapies. © 2015 Wiley Periodicals, Inc.

Electromagnetic spectrum management system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seastrand, Douglas R.

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process themore » unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.« less

Phase error statistics of a phase-locked loop synchronized direct detection optical PPM communication system

NASA Technical Reports Server (NTRS)

Natarajan, Suresh; Gardner, C. S.

1987-01-01

Receiver timing synchronization of an optical Pulse-Position Modulation (PPM) communication system can be achieved using a phased-locked loop (PLL), provided the photodetector output is suitably processed. The magnitude of the PLL phase error is a good indicator of the timing error at the receiver decoder. The statistics of the phase error are investigated while varying several key system parameters such as PPM order, signal and background strengths, and PPL bandwidth. A practical optical communication system utilizing a laser diode transmitter and an avalanche photodiode in the receiver is described, and the sampled phase error data are presented. A linear regression analysis is applied to the data to obtain estimates of the relational constants involving the phase error variance and incident signal power.

An additional study and implementation of tone calibrated technique of modulation

NASA Technical Reports Server (NTRS)

Rafferty, W.; Bechtel, L. K.; Lay, N. E.

1985-01-01

The Tone Calibrated Technique (TCT) was shown to be theoretically free from an error floor, and is only limited, in practice, by implementation constraints. The concept of the TCT transmission scheme along with a baseband implementation of a suitable demodulator is introduced. Two techniques for the generation of the TCT signal are considered: a Manchester source encoding scheme (MTCT) and a subcarrier based technique (STCT). The results are summarized for the TCT link computer simulation. The hardware implementation of the MTCT system is addressed and the digital signal processing design considerations involved in satisfying the modulator/demodulator requirements are outlined. The program findings are discussed and future direction are suggested based on conclusions made regarding the suitability of the TCT system for the transmission channel presently under consideration.

Religion and action control: Faith-specific modulation of the Simon effect but not Stop-Signal performance.

PubMed

Hommel, Bernhard; Colzato, Lorenza S; Scorolli, Claudia; Borghi, Anna M; van den Wildenberg, Wery P M

2011-08-01

Previous findings suggest that religion has a specific impact on attentional processes. Here we show that religion also affects action control. Experiment 1 compared Dutch Calvinists and Dutch atheists, matched for age, sex, intelligence, education, and cultural and socio-economic background, and Experiment 2 compared Italian Catholics with matched Italian seculars. As expected, Calvinists showed a smaller and Catholics a larger Simon effect than nonbelievers, while performance of the groups was comparable in the Stop-Signal task. This pattern suggests that religions emphasizing individualism or collectivism affects action control in specific ways, presumably by inducing chronic biases towards a more "exclusive" or "inclusive" style of decision-making. Interestingly, there was no evidence that religious practice affects inhibitory skills. Copyright © 2011 Elsevier B.V. All rights reserved.

Assessment of muscle fatigue using electromygraphm sensing

NASA Astrophysics Data System (ADS)

Helmi, Muhammad Hazimin Bin; Ping, Chew Sue; Ishak, Nur Elliza Binti; Saad, Mohd Alimi Bin Mohd; Mokhtar, Anis Shahida Niza Binti

2017-08-01

Muscle fatigue is condition of muscle decline in ability after undergoing any physical activity. Observation of the muscle condition of an athlete during training is crucial to prevent or minimize injury and able to achieve optimum performance in actual competition. The aim of this project is to develop a muscle monitoring system to detect muscle fatigue in swimming athlete. This device is capable to measure muscle stress level of the swimmer and at the same time provide indication of muscle fatigue level to trainer. Electromyography signal was recorded from the muscle movement while practicing the front crawl stroke repetitively. The time domain data was processed to frequency spectra in order to study the effect of muscle fatigue. The results show that the recorded EMG signal is able to sense muscle fatigue.

Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

PubMed

Jan, Shau-Shiun; Sun, Chih-Cheng

2010-01-01

The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

Directional guidance from audible pedestrian signals for street crossing.

PubMed

Wall, Robert S; Ashmead, Daniel H; Bentzen, Billie Louise; Barlow, Janet

2004-10-10

Typical audible pedestrian signals indicate when the pedestrian walk interval is in effect but provide little, or even misleading information for directional alignment. In three experiments, blind and blindfolded sighted adults crossed a simulated crossing with recorded traffic noise to approximate street sounds. This was done to investigate how characteristics of signal presentation affected usefulness of the auditory signal for guiding crossing behaviour. Crossing was more accurate when signals came only from the far end of the crossing rather than the typical practice of presenting signals simultaneously from both ends. Alternating the signal between ends of the crossing was not helpful. Also, the customary practice of signalling two parallel crossings at the same time drew participants somewhat toward the opposite crossing. Providing a locator tone at the end of the crossing during the pedestrian clearance interval improved crossing accuracy. These findings provide a basis for designing audible pedestrian signals to enhance directional guidance. The principal findings were the same for blind and sighted participants and applied across a range of specific signals (e.g. chirps, clicks, voices).

Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

NASA Astrophysics Data System (ADS)

Molinari, Filippo; Rosati, Samanta; Liboni, William; Negri, Emanuela; Mana, Ornella; Allais, Gianni; Benedetto, Chiara

2010-12-01

Near-infrared spectroscopy (NIRS) is a noninvasive system for the real-time monitoring of the concentration of oxygenated ([InlineEquation not available: see fulltext.]) and reduced (HHb) hemoglobin in the brain cortex. [InlineEquation not available: see fulltext.] and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls) performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20-40 mHz) and of the low frequencies (LF: 40-140 mHz). Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

Tribotronic Tuning Diode for Active Analog Signal Modulation.

PubMed

Zhou, Tao; Yang, Zhi Wei; Pang, Yaokun; Xu, Liang; Zhang, Chi; Wang, Zhong Lin

2017-01-24

Realizing active interaction with external environment/stimuli is a great challenge for current electronics. In this paper, a tribotronic tuning diode (TTD) is proposed by coupling a variable capacitance diode and a triboelectric nanogenerator in free-standing sliding mode. When the friction layer is sliding on the device surface for electrification, a reverse bias voltage is created and applied to the diode for tuning the junction capacitance. When the sliding distance increases from 0 to 25 mm, the capacitance of the TTD decreases from about 39 to 8 pF. The proposed TTD has been integrated into analog circuits and exhibited excellent performances in frequency modulation, phase shift, and filtering by sliding a finger. This work has demonstrated tunable diode and active analog signal modulation by tribotronics, which has great potential to replace ordinary variable capacitance diodes in various practical applications such as signal processing, electronic tuning circuits, precise tuning circuits, active sensor networks, electronic communications, remote controls, flexible electronics, etc.

Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model.

PubMed

Sun, Guanghao; Matsui, Takemi

2015-01-01

Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radar's respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s.

Signal and noise extraction from analog memory elements for neuromorphic computing.

PubMed

Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T

2018-05-29

Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.

Traffic signal timing manual.

DOT National Transportation Integrated Search

2008-06-01

This report serves as a comprehensive guide to traffic signal timing and documents the tasks completed in association with its : development. The focus of this document is on traffic signal control principles, practices, and procedures. It describes ...

System for monitoring an industrial or biological process

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.

1998-01-01

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

System for monitoring an industrial or biological process

DOEpatents

Gross, K.C.; Wegerich, S.W.; Vilim, R.B.; White, A.M.

1998-06-30

A method and apparatus are disclosed for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT. 49 figs.

Design of area array CCD image acquisition and display system based on FPGA

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Ning; Li, Tianting; Pan, Yue; Dai, Yuming

2014-09-01

With the development of science and technology, CCD(Charge-coupled Device) has been widely applied in various fields and plays an important role in the modern sensing system, therefore researching a real-time image acquisition and display plan based on CCD device has great significance. This paper introduces an image data acquisition and display system of area array CCD based on FPGA. Several key technical challenges and problems of the system have also been analyzed and followed solutions put forward .The FPGA works as the core processing unit in the system that controls the integral time sequence .The ICX285AL area array CCD image sensor produced by SONY Corporation has been used in the system. The FPGA works to complete the driver of the area array CCD, then analog front end (AFE) processes the signal of the CCD image, including amplification, filtering, noise elimination, CDS correlation double sampling, etc. AD9945 produced by ADI Corporation to convert analog signal to digital signal. Developed Camera Link high-speed data transmission circuit, and completed the PC-end software design of the image acquisition, and realized the real-time display of images. The result through practical testing indicates that the system in the image acquisition and control is stable and reliable, and the indicators meet the actual project requirements.

The research of laser marking control technology

NASA Astrophysics Data System (ADS)

Zhang, Qiue; Zhang, Rong

2009-08-01

In the area of Laser marking, the general control method is insert control card to computer's mother board, it can not support hot swap, it is difficult to assemble or it. Moreover, the one marking system must to equip one computer. In the system marking, the computer can not to do the other things except to transmit marking digital information. Otherwise it can affect marking precision. Based on traditional control methods existed some problems, introduced marking graphic editing and digital processing by the computer finish, high-speed digital signal processor (DSP) control marking the whole process. The laser marking controller is mainly contain DSP2812, digital memorizer, DAC (digital analog converting) transform unit circuit, USB interface control circuit, man-machine interface circuit, and other logic control circuit. Download the marking information which is processed by computer to U disk, DSP read the information by USB interface on time, then processing it, adopt the DSP inter timer control the marking time sequence, output the scanner control signal by D/A parts. Apply the technology can realize marking offline, thereby reduce the product cost, increase the product efficiency. The system have good effect in actual unit markings, the marking speed is more quickly than PCI control card to 20 percent. It has application value in practicality.

Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

PubMed Central

Coggins, Brian E.; Werner-Allen, Jonathan W.; Yan, Anthony; Zhou, Pei

2012-01-01

In structural studies of large proteins by NMR, global fold determination plays an increasingly important role in providing a first look at a target’s topology and reducing assignment ambiguity in NOESY spectra of fully-protonated samples. In this work, we demonstrate the use of ultrasparse sampling, a new data processing algorithm, and a 4-D time-shared NOESY experiment (1) to collect all NOEs in 2H/13C/15N-labeled protein samples with selectively-protonated amide and ILV methyl groups at high resolution in only four days, and (2) to calculate global folds from this data using fully automated resonance assignment. The new algorithm, SCRUB, incorporates the CLEAN method for iterative artifact removal, but applies an additional level of iteration, permitting real signals to be distinguished from noise and allowing nearly all artifacts generated by real signals to be eliminated. In simulations with 1.2% of the data required by Nyquist sampling, SCRUB achieves a dynamic range over 10000:1 (250× better artifact suppression than CLEAN) and completely quantitative reproduction of signal intensities, volumes, and lineshapes. Applied to 4-D time-shared NOESY data, SCRUB processing dramatically reduces aliasing noise from strong diagonal signals, enabling the identification of weak NOE crosspeaks with intensities 100× less than diagonal signals. Nearly all of the expected peaks for interproton distances under 5 Å were observed. The practical benefit of this method is demonstrated with structure calculations for 23 kDa and 29 kDa test proteins using the automated assignment protocol of CYANA, in which unassigned 4-D time-shared NOESY peak lists produce accurate and well-converged global fold ensembles, whereas 3-D peak lists either fail to converge or produce significantly less accurate folds. The approach presented here succeeds with an order of magnitude less sampling than required by alternative methods for processing sparse 4-D data. PMID:22946863

SU-D-207-01: Markerless Respiratory Motion Tracking with Contrast Enhanced Thoracic Cone Beam CT Projections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chao, M; Yuan, Y; Rosenzweig, K

2015-06-15

Purpose: To develop a novel technique to enhance the image contrast of clinical cone beam CT projections and extract respiratory signals based on anatomical motion using the modified Amsterdam Shroud (AS) method to benefit image guided radiation therapy. Methods: Thoracic cone beam CT projections acquired prior to treatment were preprocessed to increase their contrast for better respiratory signal extraction. Air intensity on raw images was firstly estimated and then applied to correct the projections to generate new attenuation images that were subsequently improved with deeper anatomy feature enhancement through taking logarithm operation, derivative along superior-inferior direction, respectively. All pixels onmore » individual post-processed two dimensional images were horizontally summed to one column and all projections were combined side by side to create an AS image from which patient’s respiratory signal was extracted. The impact of gantry rotation on the breathing signal rendering was also investigated. Ten projection image sets from five lung cancer patients acquired with the Varian Onboard Imager on 21iX Clinac (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Results: Application of the air correction on raw projections showed that more than an order of magnitude of contrast enhancement was achievable. The typical contrast on the raw projections is around 0.02 while that on attenuation images could greater than 0.5. Clear and stable breathing signal can be reliably extracted from the new images while the uncorrected projection sets failed to yield clear signals most of the time. Conclusion: Anatomy feature plays a key role in yielding breathing signal from the projection images using the AS technique. The air correction process facilitated the contrast enhancement significantly and attenuation images thus obtained provides a practical solution to obtaining markerless breathing motion tracking.« less

General purpose graphic processing unit implementation of adaptive pulse compression algorithms

NASA Astrophysics Data System (ADS)

Cai, Jingxiao; Zhang, Yan

2017-07-01

This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

General anesthesia selectively disrupts astrocyte calcium signaling in the awake mouse cortex

PubMed Central

Thrane, Alexander Stanley; Zeppenfeld, Douglas; Lou, Nanhong; Xu, Qiwu; Nagelhus, Erlend Arnulf; Nedergaard, Maiken

2012-01-01

Calcium signaling represents the principle pathway by which astrocytes respond to neuronal activity. General anesthetics are routinely used in clinical practice to induce a sleep-like state, allowing otherwise painful procedures to be performed. Anesthetic drugs are thought to mainly target neurons in the brain and act by suppressing synaptic activity. However, the direct effect of general anesthesia on astrocyte signaling in awake animals has not previously been addressed. This is a critical issue, because calcium signaling may represent an essential mechanism through which astrocytes can modulate synaptic activity. In our study, we performed calcium imaging in awake head-restrained mice and found that three commonly used anesthetic combinations (ketamine/xylazine, isoflurane, and urethane) markedly suppressed calcium transients in neocortical astrocytes. Additionally, all three anesthetics masked potentially important features of the astrocyte calcium signals, such as synchronized widespread transients that appeared to be associated with arousal in awake animals. Notably, anesthesia affected calcium transients in both processes and soma and depressed spontaneous signals, as well as calcium responses, evoked by whisker stimulation or agonist application. We show that these calcium transients are inositol 1,4,5-triphosphate type 2 receptor (IP3R2)-dependent but resistant to a local blockade of glutamatergic or purinergic signaling. Finally, we found that doses of anesthesia insufficient to affect neuronal responses to whisker stimulation selectively suppressed astrocyte calcium signals. Taken together, these data suggest that general anesthesia may suppress astrocyte calcium signals independently of neuronal activity. We propose that these glial effects may constitute a nonneuronal mechanism for sedative action of anesthetic drugs. PMID:23112168

Traffic signal timing manual

DOT National Transportation Integrated Search

2008-06-01

This report serves as a comprehensive guide to traffic signal timing and documents the tasks completed in association with its development. The focus of this document is on traffic signal control principles, practices, and procedures. It describes th...

Traffic signal operations handbook : second edition.

DOT National Transportation Integrated Search

2011-10-01

"This handbook provides guidelines for timing traffic control signals at intersections that operate in isolation : or as part of a coordinated signal system. The guidelines are intended to describe best practices, as identified : through interviews w...

Real-Time Detection and Tracking of Vital Signs with an Ambulatory Subject Using Millimeter-Wave Interferometry

NASA Astrophysics Data System (ADS)

Mikhelson, Ilya V.

Finding a subject's heart rate from a distance without any contact is a difficult and very practical problem. This kind of technology would allow more comfortable patient monitoring in hospitals or in home settings. It would also allow another level of security screening, as a person's heart rate increases in stressful situations, such as when lying or hiding malicious intent. In addition, the fact that the heart rate is obtained remotely means that the subject would not have to know he/she is being monitored at all, adding to the efficacy of the measurement. Using millimeter-wave interferometry, a signal can be obtained that contains composite chest wall motion made up of component motions due to cardiac activity, respiration, and interference. To be of use, these components have to be separated from each other by signal processing. To do this, the quadrature and in-phase components of the received signal are analyzed to get a displacement waveform. After that, processing can be done on that waveform in either the time or frequency domains to find the individual heartbeats. The first method is to find the power spectrum of the displacement waveform and to look for peaks corresponding to heartbeats and respiration. Another approach is to examine the signal in the time domain using wavelets for multiresolution analysis. One more method involves studying the statistics of the wavelet-processed signal. The final method uses a heartbeat model along with probabilistic processing to find heartbeats. For any of the above methods to work, the millimeter-wave sensor has to be accurately pointed at the subject's chest. However, even small subject motions can render the rest of the gathered data useless as the antenna may have lost its aim. To combat this, a color and a depth camera are used with a servo-pan/tilt base. My program finds a face in the image and subsequently tracks that face through upcoming frames. The pan/tilt base adjusts the aim of the antenna depending on the subject's position. This makes the entire system self-aiming and also allows the subject to move to a new location and to have data acquisition continue.

Optical signal processing

NASA Technical Reports Server (NTRS)

Casasent, D.

1978-01-01

The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.

Signal and Symbol: How State and Local Policies Address Data-Informed Practice

ERIC Educational Resources Information Center

Jimerson, Jo Beth; Childs, Joshua

2017-01-01

Numerous actors influence how educational policies play out in practice, but this does not mean that policies themselves are without power. Policies are crafted and enacted in part because they serve as signal and symbol: How a policy is formally codified establishes expectations, exerts norming influence, and catalyzes shifts in how issues are…

Applied digital signal processing systems for vortex flowmeter with digital signal processing.

PubMed

Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan

2009-02-01

The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems.

Implementation of Complex Signal Processing Algorithms for Position-Sensitive Microcalorimeters

NASA Technical Reports Server (NTRS)

Smith, Stephen J.

2008-01-01

We have recently reported on a theoretical digital signal-processing algorithm for improved energy and position resolution in position-sensitive, transition-edge sensor (POST) X-ray detectors [Smith et al., Nucl, lnstr and Meth. A 556 (2006) 2371. PoST's consists of one or more transition-edge sensors (TES's) on a large continuous or pixellated X-ray absorber and are under development as an alternative to arrays of single pixel TES's. PoST's provide a means to increase the field-of-view for the fewest number of read-out channels. In this contribution we extend the theoretical correlated energy position optimal filter (CEPOF) algorithm (originally developed for 2-TES continuous absorber PoST's) to investigate the practical implementation on multi-pixel single TES PoST's or Hydras. We use numerically simulated data for a nine absorber device, which includes realistic detector noise, to demonstrate an iterative scheme that enables convergence on the correct photon absorption position and energy without any a priori assumptions. The position sensitivity of the CEPOF implemented on simulated data agrees very well with the theoretically predicted resolution. We discuss practical issues such as the impact of random arrival phase of the measured data on the performance of the CEPOF. The CEPOF algorithm demonstrates that full-width-at- half-maximum energy resolution of < 8 eV coupled with position-sensitivity down to a few 100 eV should be achievable for a fully optimized device.

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

Off-Grid Direction of Arrival Estimation Based on Joint Spatial Sparsity for Distributed Sparse Linear Arrays

PubMed Central

Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin

2014-01-01

In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach. PMID:25420150

The constant current loop - A new paradigm for resistance signal conditioning

NASA Astrophysics Data System (ADS)

Anderson, Karl F.

A practical single constant current loop circuit for the signal conditioning of variable-resistance transducers has been synthesized, analyzed, and demonstrated. The strain gage and the resistance temperature device are examples of variable-resistance sensors. Lead wires connect variable-resistance sensors to remotely located signal-conditioning hardware. The presence of lead wires in the conventional Wheatstone bridge signal-conditioning circuit introduces undesired effects that reduce the quality of the data from the remote sensors. A practical approach is presented for suppressing essentially all lead wire resistance effects while indicating only the change in resistance value. An adaptation of the current loop circuit is presented that simultaneously provides an output signal voltage directly proportional to transducer resistance change and provides temperature information that is unaffected by transducer and lead wire resistance variations.

Practical applications of current loop signal conditioning

NASA Astrophysics Data System (ADS)

Anderson, Karl F.

1994-10-01

This paper describes a variety of practical application circuits based on the current loop signal conditioning paradigm. Equations defining the circuit response are also provided. The constant current loop is a fundamental signal conditioning circuit concept that can be implemented in a variety of configurations for resistance-based transducers, such as strain gages and resistance temperature devices. The circuit features signal conditioning outputs which are unaffected by extremely large variations in lead wire resistance, direct current frequency response, and inherent linearity with respect to resistance change. Sensitivity of this circuit is double that of a Wheatstone bridge circuit. Electrical output is zero for resistance change equals zero. The same excitation and output sense wires can serve multiple transducers. More application arrangements are possible with constant current loop signal conditioning than with the Wheatstone bridge.

The constant current loop - A new paradigm for resistance signal conditioning

NASA Technical Reports Server (NTRS)

Anderson, Karl F.

1993-01-01

A practical single constant current loop circuit for the signal conditioning of variable-resistance transducers has been synthesized, analyzed, and demonstrated. The strain gage and the resistance temperature device are examples of variable-resistance sensors. Lead wires connect variable-resistance sensors to remotely located signal-conditioning hardware. The presence of lead wires in the conventional Wheatstone bridge signal-conditioning circuit introduces undesired effects that reduce the quality of the data from the remote sensors. A practical approach is presented for suppressing essentially all lead wire resistance effects while indicating only the change in resistance value. An adaptation of the current loop circuit is presented that simultaneously provides an output signal voltage directly proportional to transducer resistance change and provides temperature information that is unaffected by transducer and lead wire resistance variations.

Current loop signal conditioning: Practical applications

NASA Technical Reports Server (NTRS)

Anderson, Karl F.

1995-01-01

This paper describes a variety of practical application circuits based on the current loop signal conditioning paradigm. Equations defining the circuit response are also provided. The constant current loop is a fundamental signal conditioning circuit concept that can be implemented in a variety of configurations for resistance-based transducers, such as strain gages and resistance temperature detectors. The circuit features signal conditioning outputs which are unaffected by extremely large variations in lead wire resistance, direct current frequency response, and inherent linearity with respect to resistance change. Sensitivity of this circuit is double that of a Wheatstone bridge circuit. Electrical output is zero for resistance change equals zero. The same excitation and output sense wires can serve multiple transducers. More application arrangements are possible with constant current loop signal conditioning than with the Wheatstone bridge.

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

AOD furnace splash soft-sensor in the smelting process based on improved BP neural network

NASA Astrophysics Data System (ADS)

Ma, Haitao; Wang, Shanshan; Wu, Libin; Yu, Ying

2017-11-01

In view of argon oxygen refining low carbon ferrochrome production process, in the splash of smelting process as the research object, based on splash mechanism analysis in the smelting process , using multi-sensor information fusion and BP neural network modeling techniques is proposed in this paper, using the vibration signal, the audio signal and the flame image signal in the furnace as the characteristic signal of splash, the vibration signal, the audio signal and the flame image signal in the furnace integration and modeling, and reconstruct splash signal, realize the splash soft measurement in the smelting process, the simulation results show that the method can accurately forecast splash type in the smelting process, provide a new method of measurement for forecast splash in the smelting process, provide more accurate information to control splash.

30 CFR 56.14219 - Brakeman signals.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Brakeman signals. 56.14219 Section 56.14219... Safety Practices and Operational Procedures § 56.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 56.14219 - Brakeman signals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Brakeman signals. 56.14219 Section 56.14219... Safety Practices and Operational Procedures § 56.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 57.14219 - Brakeman signals.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Brakeman signals. 57.14219 Section 57.14219... Equipment Safety Practices and Operational Procedures § 57.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 57.14219 - Brakeman signals.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Brakeman signals. 57.14219 Section 57.14219... Equipment Safety Practices and Operational Procedures § 57.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

49 CFR 218.73 - Warning signal display.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Warning signal display. 218.73 Section 218.73..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Occupied Camp Cars § 218.73 Warning signal display. (a) Warning signals, i.e., a white disk with the words “Occupied Camp Car” in black...

49 CFR 218.73 - Warning signal display.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Warning signal display. 218.73 Section 218.73..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Occupied Camp Cars § 218.73 Warning signal display. (a) Warning signals, i.e., a white disk with the words “Occupied Camp Car” in black...

49 CFR 218.73 - Warning signal display.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Warning signal display. 218.73 Section 218.73..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Occupied Camp Cars § 218.73 Warning signal display. (a) Warning signals, i.e., a white disk with the words “Occupied Camp Car” in black...

49 CFR 218.73 - Warning signal display.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Warning signal display. 218.73 Section 218.73..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Occupied Camp Cars § 218.73 Warning signal display. (a) Warning signals, i.e., a white disk with the words “Occupied Camp Car” in black...

49 CFR 218.73 - Warning signal display.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Warning signal display. 218.73 Section 218.73..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Protection of Occupied Camp Cars § 218.73 Warning signal display. (a) Warning signals, i.e., a white disk with the words “Occupied Camp Car” in black...

30 CFR 56.14219 - Brakeman signals.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Brakeman signals. 56.14219 Section 56.14219... Safety Practices and Operational Procedures § 56.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 56.14219 - Brakeman signals.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Brakeman signals. 56.14219 Section 56.14219... Safety Practices and Operational Procedures § 56.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 56.14219 - Brakeman signals.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Brakeman signals. 56.14219 Section 56.14219... Safety Practices and Operational Procedures § 56.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 57.14219 - Brakeman signals.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Brakeman signals. 57.14219 Section 57.14219... Equipment Safety Practices and Operational Procedures § 57.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 57.14219 - Brakeman signals.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Brakeman signals. 57.14219 Section 57.14219... Equipment Safety Practices and Operational Procedures § 57.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

30 CFR 57.14219 - Brakeman signals.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Brakeman signals. 57.14219 Section 57.14219... Equipment Safety Practices and Operational Procedures § 57.14219 Brakeman signals. When a train is under the direction of a brakeman and the train operator cannot clearly recognize the brakeman's signals, the train...

UWGSP7: a real-time optical imaging workstation

NASA Astrophysics Data System (ADS)

Bush, John E.; Kim, Yongmin; Pennington, Stan D.; Alleman, Andrew P.

1995-04-01

With the development of UWGSP7, the University of Washington Image Computing Systems Laboratory has a real-time workstation for continuous-wave (cw) optical reflectance imaging. Recent discoveries in optical science and imaging research have suggested potential practical use of the technology as a medical imaging modality and identified the need for a machine to support these applications in real time. The UWGSP7 system was developed to provide researchers with a high-performance, versatile tool for use in optical imaging experiments with the eventual goal of bringing the technology into clinical use. One of several major applications of cw optical reflectance imaging is tumor imaging which uses a light-absorbing dye that preferentially sequesters in tumor tissue. This property could be used to locate tumors and to identify tumor margins intraoperatively. Cw optical reflectance imaging consists of illumination of a target with a band-limited light source and monitoring the light transmitted by or reflected from the target. While continuously illuminating the target, a control image is acquired and stored. A dye is injected into a subject and a sequence of data images are acquired and processed. The data images are aligned with the control image and then subtracted to obtain a signal representing the change in optical reflectance over time. This signal can be enhanced by digital image processing and displayed in pseudo-color. This type of emerging imaging technique requires a computer system that is versatile and adaptable. The UWGSP7 utilizes a VESA local bus PC as a host computer running the Windows NT operating system and includes ICSL developed add-on boards for image acquisition and processing. The image acquisition board is used to digitize and format the analog signal from the input device into digital frames and to the average frames into images. To accommodate different input devices, the camera interface circuitry is designed in a small mezzanine board that supports the RS-170 standard. The image acquisition board is connected to the image- processing board using a direct connect port which provides a 66 Mbytes/s channel independent of the system bus. The image processing board utilizes the Texas Instruments TMS320C80 Multimedia Video Processor chip. This chip is capable of 2 billion operations per second providing the UWGSP7 with the capability to perform real-time image processing functions like median filtering, convolution and contrast enhancement. This processing power allows interactive analysis of the experiments as compared to current practice of off-line processing and analysis. Due to its flexibility and programmability, the UWGSP7 can be adapted into various research needs in intraoperative optical imaging.

Regional traffic signal operations programs : an overview

DOT National Transportation Integrated Search

2009-10-01

This report provides an overview of practices related to developing and sustaining a Regional Traffic Signal Operations Program. The purpose for a Regional Traffic Signal Operations Program is to provide regional partners a formal framework to collec...

Regional traffic signal operations programs : an overview.

DOT National Transportation Integrated Search

2009-10-01

This report provides an overview of practices related to developing and sustaining a Regional Traffic Signal Operations : Program. The purpose for a Regional Traffic Signal Operations Program is to provide regional partners a formal framework to : co...

Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

NASA Astrophysics Data System (ADS)

Wen-Bo, Wang; Xiao-Dong, Zhang; Yuchan, Chang; Xiang-Li, Wang; Zhao, Wang; Xi, Chen; Lei, Zheng

2016-01-01

In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. Project supported by the National Science and Technology, China (Grant No. 2012BAJ15B04), the National Natural Science Foundation of China (Grant Nos. 41071270 and 61473213), the Natural Science Foundation of Hubei Province, China (Grant No. 2015CFB424), the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics, China (Grant No. SOED1405), the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science, China (Grant No. Z201303), and the Hubei Key Laboratory Foundation of Transportation Internet of Things, Wuhan University of Technology, China (Grant No.2015III015-B02).

Intensity-based masking: A tool to improve functional connectivity results of resting-state fMRI.

PubMed

Peer, Michael; Abboud, Sami; Hertz, Uri; Amedi, Amir; Arzy, Shahar

2016-07-01

Seed-based functional connectivity (FC) of resting-state functional MRI data is a widely used methodology, enabling the identification of functional brain networks in health and disease. Based on signal correlations across the brain, FC measures are highly sensitive to noise. A somewhat neglected source of noise is the fMRI signal attenuation found in cortical regions in close vicinity to sinuses and air cavities, mainly in the orbitofrontal, anterior frontal and inferior temporal cortices. BOLD signal recorded at these regions suffers from dropout due to susceptibility artifacts, resulting in an attenuated signal with reduced signal-to-noise ratio in as many as 10% of cortical voxels. Nevertheless, signal attenuation is largely overlooked during FC analysis. Here we first demonstrate that signal attenuation can significantly influence FC measures by introducing false functional correlations and diminishing existing correlations between brain regions. We then propose a method for the detection and removal of the attenuated signal ("intensity-based masking") by fitting a Gaussian-based model to the signal intensity distribution and calculating an intensity threshold tailored per subject. Finally, we apply our method on real-world data, showing that it diminishes false correlations caused by signal dropout, and significantly improves the ability to detect functional networks in single subjects. Furthermore, we show that our method increases inter-subject similarity in FC, enabling reliable distinction of different functional networks. We propose to include the intensity-based masking method as a common practice in the pre-processing of seed-based functional connectivity analysis, and provide software tools for the computation of intensity-based masks on fMRI data. Hum Brain Mapp 37:2407-2418, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

PubMed Central

Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.; Ball, Kenneth R.; Lance, Brent J.

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry, STIG), which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIG method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as outperform traditional within-subject calibration techniques when limited data is available. This method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system. PMID:27713685

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface.

PubMed

Waytowich, Nicholas R; Lawhern, Vernon J; Bohannon, Addison W; Ball, Kenneth R; Lance, Brent J

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry, STIG), which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIG method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as outperform traditional within-subject calibration techniques when limited data is available. This method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.

A Practical Look at the Chemistry and Biology of Hydrogen Sulfide

PubMed Central

2012-01-01

Abstract Significance: Hydrogen sulfide (H2S) is garnering increasing interest as a biologically relevant signaling molecule. The effects of H2S have now been observed in virtually every organ system and numerous physiological processes. Recent Advances: These studies have not only opened a new field of “gasotransmitter” biology, they have also led to the development of synthetic H2S “donating” compounds with the potential to be parlayed into a variety of therapeutic applications. Critical Issues: Often lost in the exuberance of this new field is a critical examination or understanding of practical aspects of H2S chemistry and biology. This is especially notable in the areas of handling and measuring H2S, evaluating biosynthetic and metabolic pathways, and separating physiological from pharmacological responses. Future Directions: This brief review describes some of the pitfalls in H2S chemistry and biology that can lead or have already led to misleading or erroneous conclusions. The intent is to allow individuals entering or already in this burgeoning field to critically analyze the literature and to assist them in the design of future experiments. Antioxid. Redox Signal. 17, 32–44. PMID:22074253

Changes in crash risk following re-timing of traffic signal change intervals.

PubMed

Retting, Richard A; Chapline, Janella F; Williams, Allan F

2002-03-01

More than I million motor vehicle crashes occur annually at signalized intersections in the USA. The principal method used to prevent crashes associated with routine changes in signal indications is employment of a traffic signal change interval--a brief yellow and all-red period that follows the green indication. No universal practice exists for selecting the duration of change intervals, and little is known about the influence of the duration of the change interval on crash risk. The purpose of this study was to estimate potential crash effects of modifying the duration of traffic signal change intervals to conform with values associated with a proposed recommended practice published by the Institute of Transportation Engineers. A sample of 122 intersections was identified and randomly assigned to experimental and control groups. Of 51 eligible experimental sites, 40 (78%) needed signal timing changes. For the 3-year period following implementation of signal timing changes, there was an 8% reduction in reportable crashes at experimental sites relative to those occurring at control sites (P = 0.08). For injury crashes, a 12% reduction at experimental sites relative to those occurring at control sites was found (P = 0.03). Pedestrian and bicycle crashes at experimental sites decreased 37% (P = 0.03) relative to controls. Given these results and the relatively low cost of re-timing traffic signals, modifying the duration of traffic signal change intervals to conform with values associated with the Institute of Transportation Engineers' proposed recommended practice should be strongly considered by transportation agencies to reduce the frequency of urban motor vehicle crashes.

A Practice-Oriented Bifurcation Analysis for Pulse Energy Converters: A Stability Margin

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

The popularity of systems of pulse energy conversion (PEC-systems) for practical applications is due to the heightened efficiency of energy conversion processes with comparatively simple realizations. Nevertheless, a PEC-system represents a nonlinear object with a variable structure, and the bifurcation analysis remains the basic tool to describe PEC dynamics evolution. The paper is devoted to the discussion on whether the scientific viewpoint on the natural nonlinear dynamics evolution can be involved in practical applications. We focus on the problems connected with stability boundaries of an operating regime. The results of both small-signal analysis and computational bifurcation analysis are considered in the parametrical space in comparison with the results of the experimental identification of the zonal heterogeneity of the operating process. This allows to propose an adapted stability margin as a sufficiently safe distance before the point after which the operating process begins to lose the stability. Such stability margin can extend the permissible operating domain in the parametrical space at the expense of using cause-and-effect relations in the context of natural regularities of nonlinear dynamics. Reasoning and discussion are based on the experimental and computational results for a synchronous buck converter with a pulse-width modulation. The presented results can be useful, first of all, for PEC-systems with significant variation of equivalent inductance and/or capacity. We believe that the discussion supports a viewpoint by which the contemporary methods of the computational and experimental bifurcation analyses possess both analytical abilities and experimental techniques for promising solutions which could be practice-oriented for PEC-systems.

Single-channel mixed signal blind source separation algorithm based on multiple ICA processing

NASA Astrophysics Data System (ADS)

Cheng, Xiefeng; Li, Ji

2017-01-01

Take separating the fetal heart sound signal from the mixed signal that get from the electronic stethoscope as the research background, the paper puts forward a single-channel mixed signal blind source separation algorithm based on multiple ICA processing. Firstly, according to the empirical mode decomposition (EMD), the single-channel mixed signal get multiple orthogonal signal components which are processed by ICA. The multiple independent signal components are called independent sub component of the mixed signal. Then by combining with the multiple independent sub component into single-channel mixed signal, the single-channel signal is expanded to multipath signals, which turns the under-determined blind source separation problem into a well-posed blind source separation problem. Further, the estimate signal of source signal is get by doing the ICA processing. Finally, if the separation effect is not very ideal, combined with the last time's separation effect to the single-channel mixed signal, and keep doing the ICA processing for more times until the desired estimated signal of source signal is get. The simulation results show that the algorithm has good separation effect for the single-channel mixed physiological signals.

Phase Retrieval from Modulus Using Homeomorphic Signal Processing and the Complex Cepstrum: An Algorithm for Lightning Protection Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, G A

2004-06-08

In general, the Phase Retrieval from Modulus problem is very difficult. In this report, we solve the difficult, but somewhat more tractable case in which we constrain the solution to a minimum phase reconstruction. We exploit the real-and imaginary part sufficiency properties of the Fourier and Hilbert Transforms of causal sequences to develop an algorithm for reconstructing spectral phase given only spectral modulus. The algorithm uses homeomorphic signal processing methods with the complex cepstrum. The formal problem of interest is: Given measurements of only the modulus {vert_bar}H(k){vert_bar} (no phase) of the Discrete Fourier Transform (DFT) of a real, finite-length, stable,more » causal time domain signal h(n), compute a minimum phase reconstruction {cflx h}(n) of the signal. Then compute the phase of {cflx h}(n) using a DFT, and exploit the result as an estimate of the phase of h(n). The development of the algorithm is quite involved, but the final algorithm and its implementation are very simple. This work was motivated by a Phase Retrieval from Modulus Problem that arose in LLNL Defense Sciences Engineering Division (DSED) projects in lightning protection for buildings. The measurements are limited to modulus-only spectra from a spectrum analyzer. However, it is desired to perform system identification on the building to compute impulse responses and transfer functions that describe the amount of lightning energy that will be transferred from the outside of the building to the inside. This calculation requires knowledge of the entire signals (both modulus and phase). The algorithm and software described in this report are proposed as an approach to phase retrieval that can be used for programmatic needs. This report presents a brief tutorial description of the mathematical problem and the derivation of the phase retrieval algorithm. The efficacy of the theory is demonstrated using simulated signals that meet the assumptions of the algorithm. We see that for the noiseless case, the reconstructions are extremely accurate. When moderate to heavy simulated white Gaussian noise was added, the algorithm performance remained reasonably robust, especially in the low frequency part of the spectrum, which is the part of most interest for lightning protection. Limitations of the algorithm include the following: (1) It does not account for noise in the given spectral modulus. Fortunately, the lightning protection signals of interest generally have a reasonably high signal-to-noise ratio (SNR). (2) The DFT length N must be even and larger than the length of the nonzero part of the measured signals. These constraints are simple to meet in practice. (3) Regardless of the properties of the actual signal h(n), the phase retrieval results are constrained to have the minimum phase property. In most problems of practical interest, these assumptions are very reasonable and probably valid. They are reasonable assumptions for Lightning Protection applications. Proposed future work includes (a) Evaluating the efficacy of the algorithm with real Lightning Protection signals from programmatic applications, (b) Performing a more rigorous analysis of noise effects, (c) Using the algorithm along with advanced system identification algorithms to estimate impulse responses and transfer functions, (d) Developing algorithms to deal with measured partial (truncated) spectral moduli, and (e) R & D of phase retrieval algorithms that specifically deal with general (not necessarily minimum phase) signals, and noisy spectral moduli.« less

Manual on performance of traffic signal systems: assessment of operations and maintenance : [summary].

DOT National Transportation Integrated Search

2017-05-01

In this project, Florida Atlantic University researchers developed a methodology and software tools that allow objective, quantitative analysis of the performance of signal systems. : The researchers surveyed the state of practice for traffic signal ...

Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

PubMed

Tulsyan, Aditya; Garvin, Christopher; Ündey, Cenk

2018-04-06

Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monitoring (BPM) platforms have been in use in recent years to ensure comprehensive monitoring is in place as a complementary tool for continued process verification to detect weak signals. This article addresses a longstanding, industry-wide problem in BPM, referred to as the "Low-N" problem, wherein a product has a limited production history. The current best industrial practice to address the Low-N problem is to switch from a multivariate to a univariate BPM, until sufficient product history is available to build and deploy a multivariate BPM platform. Every batch run without a robust multivariate BPM platform poses risk of not detecting potential weak signals developing in the process that might have an impact on process and product performance. In this article, we propose an approach to solve the Low-N problem by generating an arbitrarily large number of in silico batches through a combination of hardware exploitation and machine-learning methods. To the best of authors' knowledge, this is the first article to provide a solution to the Low-N problem in biopharmaceutical manufacturing using machine-learning methods. Several industrial case studies from bulk drug substance manufacturing are presented to demonstrate the efficacy of the proposed approach for BPM under various Low-N scenarios. © 2018 Wiley Periodicals, Inc.

Challenges in Extracting Information From Large Hydrogeophysical-monitoring Datasets

NASA Astrophysics Data System (ADS)

Day-Lewis, F. D.; Slater, L. D.; Johnson, T.

2012-12-01

Over the last decade, new automated geophysical data-acquisition systems have enabled collection of increasingly large and information-rich geophysical datasets. Concurrent advances in field instrumentation, web services, and high-performance computing have made real-time processing, inversion, and visualization of large three-dimensional tomographic datasets practical. Geophysical-monitoring datasets have provided high-resolution insights into diverse hydrologic processes including groundwater/surface-water exchange, infiltration, solute transport, and bioremediation. Despite the high information content of such datasets, extraction of quantitative or diagnostic hydrologic information is challenging. Visual inspection and interpretation for specific hydrologic processes is difficult for datasets that are large, complex, and (or) affected by forcings (e.g., seasonal variations) unrelated to the target hydrologic process. New strategies are needed to identify salient features in spatially distributed time-series data and to relate temporal changes in geophysical properties to hydrologic processes of interest while effectively filtering unrelated changes. Here, we review recent work using time-series and digital-signal-processing approaches in hydrogeophysics. Examples include applications of cross-correlation, spectral, and time-frequency (e.g., wavelet and Stockwell transforms) approaches to (1) identify salient features in large geophysical time series; (2) examine correlation or coherence between geophysical and hydrologic signals, even in the presence of non-stationarity; and (3) condense large datasets while preserving information of interest. Examples demonstrate analysis of large time-lapse electrical tomography and fiber-optic temperature datasets to extract information about groundwater/surface-water exchange and contaminant transport.

A Frequency-Domain Multipath Parameter Estimation and Mitigation Method for BOC-Modulated GNSS Signals

PubMed Central

Sun, Chao; Feng, Wenquan; Du, Songlin

2018-01-01

As multipath is one of the dominating error sources for high accuracy Global Navigation Satellite System (GNSS) applications, multipath mitigation approaches are employed to minimize this hazardous error in receivers. Binary offset carrier modulation (BOC), as a modernized signal structure, is adopted to achieve significant enhancement. However, because of its multi-peak autocorrelation function, conventional multipath mitigation techniques for binary phase shift keying (BPSK) signal would not be optimal. Currently, non-parametric and parametric approaches have been studied specifically aiming at multipath mitigation for BOC signals. Non-parametric techniques, such as Code Correlation Reference Waveforms (CCRW), usually have good feasibility with simple structures, but suffer from low universal applicability for different BOC signals. Parametric approaches can thoroughly eliminate multipath error by estimating multipath parameters. The problems with this category are at the high computation complexity and vulnerability to the noise. To tackle the problem, we present a practical parametric multipath estimation method in the frequency domain for BOC signals. The received signal is transferred to the frequency domain to separate out the multipath channel transfer function for multipath parameter estimation. During this process, we take the operations of segmentation and averaging to reduce both noise effect and computational load. The performance of the proposed method is evaluated and compared with the previous work in three scenarios. Results indicate that the proposed averaging-Fast Fourier Transform (averaging-FFT) method achieves good robustness in severe multipath environments with lower computational load for both low-order and high-order BOC signals. PMID:29495589

Basic research on machinery fault diagnostics: Past, present, and future trends

NASA Astrophysics Data System (ADS)

Chen, Xuefeng; Wang, Shibin; Qiao, Baijie; Chen, Qiang

2018-06-01

Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.

Electrophysiological measurement of human auditory function

NASA Technical Reports Server (NTRS)

Galambos, R.

1975-01-01

Knowledge of the human auditory evoked response is reviewed, including methods of determining this response, the way particular changes in the stimulus are coupled to specific changes in the response, and how the state of mind of the listener will influence the response. Important practical applications of this basic knowledge are discussed. Measurement of the brainstem evoked response, for instance, can state unequivocally how well the peripheral auditory apparatus functions. It might then be developed into a useful hearing test, especially for infants and preverbal or nonverbal children. Clinical applications of measuring the brain waves evoked 100 msec and later after the auditory stimulus are undetermined. These waves are clearly related to brain events associated with cognitive processing of acoustic signals, since their properties depend upon where the listener directs his attention and whether how long he expects the signal.

Recommendations for the standardization and interpretation of the electrocardiogram. Part I: The electrocardiogram and its technology. A scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society.

PubMed

Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S

2007-03-01

This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.

FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing

NASA Technical Reports Server (NTRS)

Berner, Stephan; DeLeon, Phillip

1999-01-01

One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.

Study of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors with varying pixel sizes

NASA Astrophysics Data System (ADS)

Ocampo Giraldo, L.; Bolotnikov, A. E.; Camarda, G. S.; De Geronimo, G.; Fried, J.; Gul, R.; Hodges, D.; Hossain, A.; Ünlü, K.; Vernon, E.; Yang, G.; James, R. B.

2018-03-01

We evaluated the sub-pixel position resolution achievable in large-volume CdZnTe pixelated detectors with conventional pixel patterns and for several different pixel sizes: 2.8 mm, 1.72 mm, 1.4 mm and 0.8 mm. Achieving position resolution below the physical dimensions of pixels (sub-pixel resolution) is a practical path for making high-granularity position-sensitive detectors, <100 μm, using a limited number of pixels dictated by the mechanical constraints and multi-channel readout electronics. High position sensitivity is important for improving the imaging capability of CZT gamma cameras. It also allows for making more accurate corrections of response non-uniformities caused by crystal defects, thus enabling use of standard-grade (unselected) and less expensive CZT crystals for producing large-volume position-sensitive CZT detectors feasible for many practical applications. We analyzed the digitized charge signals from a representative 9 pixels and the cathode, generated using a pulsed-laser light beam focused down to 10 μm (650 nm) to scan over a selected 3 × 3 pixel area. We applied our digital pulse processing technique to the time-correlated signals captured from adjacent pixels to achieve and evaluate the capability for sub-pixel position resolution. As an example, we also demonstrated an application of 3D corrections to improve the energy resolution and positional information of the events for the tested detectors.

Study of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors with varying pixel sizes

DOE PAGES

Giraldo, L. Ocampo; Bolotnikov, A. E.; Camarda, G. S.; ...

2017-12-18

Here, we evaluated the sub-pixel position resolution achievable in large-volume CdZnTe pixelated detectors with conventional pixel patterns and for several different pixel sizes: 2.8 mm, 1.72 mm, 1.4 mm and 0.8 mm. Achieving position resolution below the physical dimensions of pixels (sub-pixel resolution) is a practical path for making high-granularity position-sensitive detectors, <100 μμm, using a limited number of pixels dictated by the mechanical constraints and multi-channel readout electronics. High position sensitivity is important for improving the imaging capability of CZT gamma cameras. It also allows for making more accurate corrections of response non-uniformities caused by crystal defects, thus enablingmore » use of standard-grade (unselected) and less expensive CZT crystals for producing large-volume position-sensitive CZT detectors feasible for many practical applications. We analyzed the digitized charge signals from a representative 9 pixels and the cathode, generated using a pulsed-laser light beam focused down to 10 m (650 nm) to scan over a selected 3×3 pixel area. We applied our digital pulse processing technique to the time-correlated signals captured from adjacent pixels to achieve and evaluate the capability for sub-pixel position resolution. As an example, we also demonstrated an application of 3D corrections to improve the energy resolution and positional information of the events for the tested detectors.« less

Triplex DNA formation-mediated strand displacement reaction for highly sensitive fluorescent detection of melamine.

PubMed

Liu, Xiaojuan; Xu, Ningning; Gai, Panpan; Li, Feng

2018-08-01

Since melamine is a strong hazard to human health, the development of new methods for highly sensitive detection of melamine is highly desirable. Herein, a novel fluorescent biosensing strategy was designed for sensitive and selective melamine assay based on the recognition ability of abasic (AP) site in triplex towards melamine and signal amplification by Mg 2+ -dependent DNAzyme. In this strategy, the melamine-induced formation of triplex DNA was employed to trigger the strand displacement reaction (SDR). The SDR process converted the specific target recognition into the release and activation of Mg 2+ -dependent DNAzyme, which could catalyze the cleavage of fluorophore/quencher labeled DNA substrate (FQ), resulting in a significantly increased fluorescent signal. Under the optimal conditions, the fluorescent signal has a linear relationship with the logarithm of the melamine concentration in a wide range of 0.005-50 μM. The detection limit was estimated to be 0.9 nM (0.1ppb), which is sufficiently sensitive for practical application. Furthermore, this strategy exhibits high selectivity against other potential interfering substances, and the practical application of this strategy for milk samples reveals that the proposed strategy works well for melamine assay in real samples. Therefore, this strategy presents a new method for the sensitive melamine assay and holds great promise for sensing applications in the environment and the food safety field. Copyright © 2018 Elsevier B.V. All rights reserved.

Study of sub-pixel position resolution with time-correlated transient signals in 3D pixelated CdZnTe detectors with varying pixel sizes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giraldo, L. Ocampo; Bolotnikov, A. E.; Camarda, G. S.

Here, we evaluated the sub-pixel position resolution achievable in large-volume CdZnTe pixelated detectors with conventional pixel patterns and for several different pixel sizes: 2.8 mm, 1.72 mm, 1.4 mm and 0.8 mm. Achieving position resolution below the physical dimensions of pixels (sub-pixel resolution) is a practical path for making high-granularity position-sensitive detectors, <100 μμm, using a limited number of pixels dictated by the mechanical constraints and multi-channel readout electronics. High position sensitivity is important for improving the imaging capability of CZT gamma cameras. It also allows for making more accurate corrections of response non-uniformities caused by crystal defects, thus enablingmore » use of standard-grade (unselected) and less expensive CZT crystals for producing large-volume position-sensitive CZT detectors feasible for many practical applications. We analyzed the digitized charge signals from a representative 9 pixels and the cathode, generated using a pulsed-laser light beam focused down to 10 m (650 nm) to scan over a selected 3×3 pixel area. We applied our digital pulse processing technique to the time-correlated signals captured from adjacent pixels to achieve and evaluate the capability for sub-pixel position resolution. As an example, we also demonstrated an application of 3D corrections to improve the energy resolution and positional information of the events for the tested detectors.« less

Signal and image processing algorithm performance in a virtual and elastic computing environment

NASA Astrophysics Data System (ADS)

Bennett, Kelly W.; Robertson, James

2013-05-01

The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.

Surface Enhanced Raman Spectroscopy (SERS) and multivariate analysis as a screening tool for detecting Sudan I dye in culinary spices

NASA Astrophysics Data System (ADS)

Di Anibal, Carolina V.; Marsal, Lluís F.; Callao, M. Pilar; Ruisánchez, Itziar

2012-02-01

Raman spectroscopy combined with multivariate analysis was evaluated as a tool for detecting Sudan I dye in culinary spices. Three Raman modalities were studied: normal Raman, FT-Raman and SERS. The results show that SERS is the most appropriate modality capable of providing a proper Raman signal when a complex matrix is analyzed. To get rid of the spectral noise and background, Savitzky-Golay smoothing with polynomial baseline correction and wavelet transform were applied. Finally, to check whether unadulterated samples can be differentiated from samples adulterated with Sudan I dye, an exploratory analysis such as principal component analysis (PCA) was applied to raw data and data processed with the two mentioned strategies. The results obtained by PCA show that Raman spectra need to be properly treated if useful information is to be obtained and both spectra treatments are appropriate for processing the Raman signal. The proposed methodology shows that SERS combined with appropriate spectra treatment can be used as a practical screening tool to distinguish samples suspicious to be adulterated with Sudan I dye.

Physiological regulation through learnt control of appetites by contingencies among signals from external and internal environments.

PubMed

Booth, David A

2008-11-01

As reviewed by [Cooper, S. J. (2008). From Claude Bernard to Walter Cannon: emergence of the concept of homeostasis. Appetite 51, 419-27.] Claude Bernard's idea of stabilisation of bodily states, as realised in Walter B. Cannon's conception of homeostasis, took mathematical form during the 1940s in the principle that externally originating disturbance of a physiological parameter can feed an informative signal around the brain to trigger counteractive processes--a corrective mechanism known as negative feedback, in practice reliant on feedforward. Three decades later, enough was known of the physiology and psychology of eating and drinking for calculations to show how experimentally demonstrated mechanisms of feedforward that had been learnt from negative feedback combine to regulate exchanges of water and energy between the body and the surroundings. Subsequent systemic physiology, molecular neuroscience and experimental psychology, however, have been traduced by a misconception that learnt controls of intake are 'non-homeostatic', the myth of biological 'set points' and an historic failure to address evidence for the ingestion-adapting information-processing mechanisms on which an operationally integrative theory of eating and drinking relies.

Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis

NASA Astrophysics Data System (ADS)

Shi, Z. M.; Liu, L.; Peng, M.; Liu, C. C.; Tao, F. J.; Liu, C. S.

2018-04-01

Full-length bonded rock bolts are commonly used in mining, tunneling and slope engineering because of their simple design and resistance to corrosion. However, the length of a rock bolt and grouting quality do not often meet the required design standards in practice because of the concealment and complexity of bolt construction. Non-destructive testing is preferred when testing a rock bolt's quality because of the convenience, low cost and wide detection range. In this paper, a signal analysis method for the non-destructive sound wave testing of full-length bonded rock bolts is presented, which is based on the Hilbert-Huang transform (HHT). First, we introduce the HHT analysis method to calculate the bolt length and identify defect locations based on sound wave reflection test signals, which includes decomposing the test signal via empirical mode decomposition (EMD), selecting the intrinsic mode functions (IMF) using the Pearson Correlation Index (PCI) and calculating the instantaneous phase and frequency via the Hilbert transform (HT). Second, six model tests are conducted using different grouting defects and bolt protruding lengths to verify the effectiveness of the HHT analysis method. Lastly, the influence of the bolt protruding length on the test signal, identification of multiple reflections from defects, bolt end and protruding end, and mode mixing from EMD are discussed. The HHT analysis method can identify the bolt length and grouting defect locations from signals that contain noise at multiple reflected interfaces. The reflection from the long protruding end creates an irregular test signal with many frequency peaks on the spectrum. The reflections from defects barely change the original signal because they are low energy, which cannot be adequately resolved using existing methods. The HHT analysis method can identify reflections from the long protruding end of the bolt and multiple reflections from grouting defects based on mutations in the instantaneous frequency, which makes weak reflections more noticeable. The mode mixing phenomenon is observed in several tests, but this does not markedly affect the identification results due to the simple medium in bolt tests. The mode mixing can be reduced by ensemble EMD (EEMD) or complete ensemble EMD with adaptive noise (CEEMDAN), which are powerful tools to used analyze the test signal in a complex medium and may play an important role in future studies. The HHT bolt signal analysis method is a self-adaptive and automatic process, which can be programed as analysis software and will make bolt tests more convenient in practice.

Signal Quality and the Reliability of Seismic Observations

NASA Astrophysics Data System (ADS)

Zeiler, C. P.; Velasco, A. A.; Pingitore, N. E.

2009-12-01

The ability to detect, time and measure seismic phases depends on the location, size, and quality of the recorded signals. Additional constraints are an analyst’s familiarity with a seismogenic zone and with the seismic stations that record the energy. Quantification and qualification of an analyst’s ability to detect, time and measure seismic signals has not been calculated or fully assessed. The fundamental measurement for computing the accuracy of a seismic measurement is the signal quality. Several methods have been proposed to measure signal quality; however, the signal-to-noise ratio (SNR) has been adopted as a short-term average over the long-term average. While the standard SNR is an easy and computationally inexpensive term, the overall statistical significance has not been computed for seismic measurement analysis. The prospect of canonizing the process of cataloging seismic arrivals hinges on the ability to repeat measurements made by different methods and analysts. The first step in canonizing phase measurements has been done by the IASPEI, which established a reference for accepted practices in naming seismic phases. The New Manual for Seismological Observatory Practices (NMSOP, 2002) outlines key observations for seismic phases recorded at different distances and proposes to quantify timing uncertainty with a user-specified windowing technique. However, this added measurement would not completely remove bias introduced by different techniques used by analysts to time seismic arrivals. The general guideline to time a seismic arrival is to record the time where a noted change in frequency and/or amplitude begins. This is generally achieved by enhancing the arrivals through filtering or beam forming. However, these enhancements can alter the characteristics of the arrival and how the arrival will be measured. Furthermore, each enhancement has user-specified parameters that can vary between analysts and this results in reduced ability to repeat measurements between analysts. The SPEAR project (Zeiler and Velasco, 2009) has started to explore the effects of comparing measurements from the same seismograms. Initial results showed that experience and the signal quality are the leading contributors to pick differences. However, the traditional SNR method of measuring signal quality was replaced by a Wide-band Spectral Ratio (WSR) due to a decrease in scatter. This observation brings up an important question of what is the best way to measure signal quality. We compare various methods (traditional SNR, WSR, power spectral density plots, Allan Variance) that have been proposed to measure signal quality and discuss which method provides the best tool to compare arrival time uncertainty.

A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals.

PubMed

Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K; Birch, Gary E

2007-06-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

TOPICAL REVIEW: A survey of signal processing algorithms in brain computer interfaces based on electrical brain signals

NASA Astrophysics Data System (ADS)

Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.

2007-06-01

Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

Improvements in Speed and Functionality of a 670-GHz Imaging Radar

NASA Technical Reports Server (NTRS)

Dengler, Robert J.; Cooper, Ken B.; Mehdi, Imran; Siegel, Peter H.; Tarsala, Jan A.; Bryllert, Thomas E.

2011-01-01

Significant improvements have been made in the instrument originally described in a prior NASA Tech Briefs article: Improved Speed and Functionality of a 580-GHz Imaging Radar (NPO-45156), Vol. 34, No. 7 (July 2010), p. 51. First, the wideband YIG oscillator has been replaced with a JPL-designed and built phase-locked, low-noise chirp source. Second, further refinements to the data acquisition and signal processing software have been performed by moving critical code sections to C code, and compiling those sections to Windows DLLs, which are then invoked from the main LabVIEW executive. This system is an active, single-pixel scanned imager operating at 670 GHz. The actual chirp signals for the RF and LO chains were generated by a pair of MITEQ 2.5 3.3 GHz chirp sources. Agilent benchtop synthesizers operating at fixed frequencies around 13 GHz were then used to up-convert the chirp sources to 15.5 16.3 GHz. The resulting signals were then multiplied 36 times by a combination of off-the-shelf millimeter- wave components, and JPL-built 200- GHz doublers and 300- and 600-GHz triplers. The power required to drive the submillimeter-wave multipliers was provided by JPL-built W-band amplifiers. The receive and transmit signal paths were combined using a thin, high-resistivity silicon wafer as a beam splitter. While the results at present are encouraging, the system still lacks sufficient speed to be usable for practical applications in a contraband detection. Ideally, an image acquisition speed of ten seconds, or a factor of 30 improvement, is desired. However, the system improvements to date have resulted in a factor of five increase in signal acquisition speed, as well as enhanced signal processing algorithms, permitting clearer imaging of contraband objects hidden underneath clothing. In particular, advances in three distinct areas have enabled these performance enhancements: base source phase noise reduction, chirp rate, and signal processing. Additionally, a second pixel was added, automatically reducing the imaging time by a factor of two. Although adding a second pixel to the system doubles the amount of submillimeter components required, some savings in microwave hardware can be realized by using a common low-noise source.

Signal Timing and Coordination Strategies Under Varying Traffic Demands

DOT National Transportation Integrated Search

2012-07-01

Current practice for signal timing and signal coordination is to develop and operate a limited number of predetermined time-of-day plans. Coordination plans are commonly developed for and based on weekday morning, mid-day, evening, and weekend peak p...

Practical application of a bidirectional microwave photonic filter: simultaneous transmission of analog TV signals

NASA Astrophysics Data System (ADS)

Correa-Mena, Ana Gabriela; Zaldívar-Huerta, Ignacio E.; Abril García, Jose Humberto; García-Juárez, Alejandro; Vera-Marquina, Alicia

2016-10-01

A practical application of a bidirectional microwave photonic filter (MPF) to transmit simultaneous analog TV signals coded on microwave carriers is experimentally demonstrated. The frequency response of the bidirectional MPF is obtained by the interaction of an externally modulated multimode laser diode emitting at 1.55 μm associated to the free-spectral range of the optical source, the chromatic dispersion parameter of the optical fiber, as well as the length of the optical link. The filtered microwave bandpass window generated around 2 GHz is used as electrical carrier in order to simultaneously transmit TV signals of 67.25 and 61.25 MHz in both directions. The obtained signal-to-noise ratios for the transmitted signals of 67.25 and 61.25 MHz are 37.62 and 44.77 dB, respectively.

Analysis of thin fractures with GPR: from theory to practice

NASA Astrophysics Data System (ADS)

Arosio, Diego; Zanzi, Luigi; Longoni, Laura; Papini, Monica

2017-04-01

Whenever we perform a GPR survey to investigate a rocky medium, being the ultimate purpose of the survey either to study the stability of a rock slope or to determine the soundness of a quarried rock block, we would like mainly to detect any fracture within the investigated medium and, possibly, to estimate the parameters of the fractures, namely thickness and filling material. In most of the practical cases, rock fracture thicknesses are very small when compared to the wavelength of the electromagnetic radiation generated by the GPR systems. In such cases, fractures are to be considered as thin beds, i.e. two interfaces whose distance is smaller than GPR resolving capability, and the reflected signal is the sum of the electromagnetic reverberation within the bed. According to this, fracture parameters are encoded in the thin bed complex response and in this work we propose a methodology based on deterministic deconvolution to process amplitude and phase information in the frequency domain to estimate fracture parameters. We first present some theoretical aspects related to thin bed response and a sensitivity analysis concerning fracture thickness and filling. Secondly, we deal with GPR datasets collected both during laboratory experiments and in the facilities of quarrying activities. In the lab tests fractures were simulated by placing materials with known electromagnetic parameters and controlled thickness in between two small marble blocks, whereas field GPR surveys were performed on bigger quarried ornamental stone blocks before they were submitted to the cutting process. We show that, with basic pre-processing and the choice of a proper deconvolving signal, results are encouraging although an ambiguity between thickness and filling estimates exists when no a-priori information is available. Results can be improved by performing CMP radar surveys that are able to provide additional information (i.e., variation of thin bed response versus offset) at the expense of acquisition effort and of more complex and tricky pre-processing sequences.

Lifetime evaluation of large format CMOS mixed signal infrared devices

NASA Astrophysics Data System (ADS)

Linder, A.; Glines, Eddie

2015-09-01

New large scale foundry processes continue to produce reliable products. These new large scale devices continue to use industry best practice to screen for failure mechanisms and validate their long lifetime. The Failure-in-Time analysis in conjunction with foundry qualification information can be used to evaluate large format device lifetimes. This analysis is a helpful tool when zero failure life tests are typical. The reliability of the device is estimated by applying the failure rate to the use conditions. JEDEC publications continue to be the industry accepted methods.

Analysis of a novel sensor interrogation technique based on fiber cavity ring-down (CRD) loop and OTDR

NASA Astrophysics Data System (ADS)

Yüksel, Kivilcim; Yilmaz, Anil

2018-07-01

We present the analysis of a remote sensor based on fiber Cavity Ring-Down (CRD) loop interrogated by an Optical Time Domain Reflectometer (OTDR) taking into account both practical limitations and the related signal processing. A commercial OTDR is used for both pulse generation and sensor output detection. This allows obtaining a compact and simple design for intensity-based sensor applications. This novel sensor interrogation approach is experimentally demonstrated by placing a variable attenuator inside the fiber loop that mimics a sensor head.

Symposium on Signal and Image Processing English-Language Abstracts (12th) Held in Juan-Les-Pins, France on 12-16 June 1989

DTIC Science & Technology

1989-12-01

Neril1" (’)INFOCOM Dpt., via Eudossiana 18, 1-00184 Roma, Italy (2) CONTRAVES Italiana SpA. via Affile 102, 1-00139 Roma, Italy SUMMARY The paper...central processor. This makes the perception of the system less accurate and induces a loss in performance. Previous studies have considered the case...current practice. An inner code, often decoded using a weighted input, is concatenated with an outer code decoded without such a weighting . If

Is complex signal processing for bone conduction hearing aids useful?

PubMed

Kompis, Martin; Kurz, Anja; Pfiffner, Flurin; Senn, Pascal; Arnold, Andreas; Caversaccio, Marco

2014-05-01

To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

Digital Signal Processing Based Biotelemetry Receivers

NASA Technical Reports Server (NTRS)

Singh, Avtar; Hines, John; Somps, Chris

1997-01-01

This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.

Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

NASA Astrophysics Data System (ADS)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

Robust detection of heartbeats using association models from blood pressure and EEG signals.

PubMed

Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol

2016-01-15

The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data association method of supplementing ECG with a variety of physiological signals and accounting for the patient-specific lag between different pulsatile signals and ECG. Multimodal signal detectors and data-fusion approaches such as those proposed in this article can reduce false alarms and improve patient monitoring.

Device and method to enhance availability of cluster-based processing systems

NASA Technical Reports Server (NTRS)

Lupia, David J. (Inventor); Ramos, Jeremy (Inventor); Samson, Jr., John R. (Inventor)

2010-01-01

An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.

Across-channel interference in intensity discrimination: The role of practice and listening strategy

PubMed Central

Buss, Emily

2008-01-01

Pure tone intensity discrimination thresholds can be elevated by the introduction of remote maskers with roved level. This effect is on the order of 10 dB [10log(ΔI/I)] in some conditions and can be demonstrated under conditions of little or no energetic masking. The current study examined the effect of practice and observer strategy on this phenomenon. Experiment 1 included observers who had no formal experience with intensity discrimination and provided training over six hours on a single masked intensity discrimination task to assess learning effects. Thresholds fell with practice for most observers, with significant improvements in 6 out of 8 cases. Despite these improvements significant masking remained in all cases. The second experiment assessed trial-by-trial effects of roved masker level. Conditional probability of a ‘signal-present’ response as a function of the rove value assigned to each of the two masker tones indicates fundamental differences among observers’ processing strategies, even after six hours of practice. The variability in error patterns across practiced listeners suggests that observers approach the task differently, though this variability does not appear to be related to sensitivity. PMID:18177156

EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study

PubMed Central

2013-01-01

Background Several studies investigating the use of electromyographic (EMG) signals in robot-based stroke neuro-rehabilitation to enhance functional recovery. Here we explored whether a classical EMG-based patterns recognition approach could be employed to predict patients’ intentions while attempting to generate goal-directed movements in the horizontal plane. Methods Nine right-handed healthy subjects and seven right-handed stroke survivors performed reaching movements in the horizontal plane. EMG signals were recorded and used to identify the intended motion direction of the subjects. To this aim, a standard pattern recognition algorithm (i.e., Support Vector Machine, SVM) was used. Different tests were carried out to understand the role of the inter- and intra-subjects’ variability in affecting classifier accuracy. Abnormal muscular spatial patterns generating misclassification were evaluated by means of an assessment index calculated from the results achieved with the PCA, i.e., the so-called Coefficient of Expressiveness (CoE). Results Processing the EMG signals of the healthy subjects, in most of the cases we were able to build a static functional map of the EMG activation patterns for point-to-point reaching movements on the horizontal plane. On the contrary, when processing the EMG signals of the pathological subjects a good classification was not possible. In particular, patients’ aimed movement direction was not predictable with sufficient accuracy either when using the general map extracted from data of normal subjects and when tuning the classifier on the EMG signals recorded from each patient. Conclusions The experimental findings herein reported show that the use of EMG patterns recognition approach might not be practical to decode movement intention in subjects with neurological injury such as stroke. Rather than estimate motion from EMGs, future scenarios should encourage the utilization of these signals to detect and interpret the normal and abnormal muscle patterns and provide feedback on their correct recruitment. PMID:23855907

System and method for investigating sub-surface features of a rock formation with acoustic sources generating coded signals

DOEpatents

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A; Guyer, Robert; Ten Cate, James A; Le Bas, Pierre-Yves; Larmat, Carene S

2014-12-30

A system and a method for investigating rock formations includes generating, by a first acoustic source, a first acoustic signal comprising a first plurality of pulses, each pulse including a first modulated signal at a central frequency; and generating, by a second acoustic source, a second acoustic signal comprising a second plurality of pulses. A receiver arranged within the borehole receives a detected signal including a signal being generated by a non-linear mixing process from the first-and-second acoustic signal in a non-linear mixing zone within the intersection volume. The method also includes-processing the received signal to extract the signal generated by the non-linear mixing process over noise or over signals generated by a linear interaction process, or both.

Intelligent processing of acoustic emission signals

NASA Astrophysics Data System (ADS)

Sachse, Wolfgang; Grabec, Igor

1992-07-01

Recent developments in applying neural-like signal-processing procedures for analyzing acoustic emission signals are summarized. These procedures employ a set of learning signals to develop a memory that can subsequently be utilized to process other signals to recover information about an unknown source. A majority of the current applications to process ultrasonic waveforms are based on multilayered, feed-forward neural networks, trained with some type of back-error propagation rule.

Noise analysis for near-field 3D FM-CW radar imaging systems

NASA Astrophysics Data System (ADS)

Sheen, David M.

2015-05-01

Near field radar imaging systems are used for demanding security applications including concealed weapon detection in airports and other high-security venues. Despite the near-field operation, phase noise and thermal noise can limit performance in several ways. Practical imaging systems can employ arrays with low gain antennas and relatively large signal distribution networks that have substantial losses which limit transmit power and increase the effective noise figure of the receiver chain, resulting in substantial thermal noise. Phase noise can also limit system performance. The signal coupled from transmitter to receiver is much larger than expected target signals. Phase noise from this coupled signal can set the system noise floor if the oscillator is too noisy. Frequency modulated continuous wave (FM-CW) radar transceivers used in short range systems are relatively immune to the effects of the coupled phase noise due to range correlation effects. This effect can reduce the phase-noise floor such that it is below the thermal noise floor for moderate performance oscillators. Phase noise is also manifested in the range response around bright targets, and can cause smaller targets to be obscured. Noise in synthetic aperture imaging systems is mitigated by the processing gain of the system. In this paper, the effects of thermal noise, phase noise, and processing gain are analyzed in the context of a near field 3-D FM-CW imaging radar as might be used for concealed weapon detection. In addition to traditional frequency domain analysis, a time-domain simulation is employed to graphically demonstrate the effect of these noise sources on a fast-chirping FM-CW system.

Determining Aliasing in Isolated Signal Conditioning Modules

NASA Technical Reports Server (NTRS)

2009-01-01

The basic concept of aliasing is this: Converting analog data into digital data requires sampling the signal at a specific rate, known as the sampling frequency. The result of this conversion process is a new function, which is a sequence of digital samples. This new function has a frequency spectrum, which contains all the frequency components of the original signal. The Fourier transform mathematics of this process show that the frequency spectrum of the sequence of digital samples consists of the original signal s frequency spectrum plus the spectrum shifted by all the harmonics of the sampling frequency. If the original analog signal is sampled in the conversion process at a minimum of twice the highest frequency component contained in the analog signal, and if the reconstruction process is limited to the highest frequency of the original signal, then the reconstructed signal accurately duplicates the original analog signal. It is this process that can give birth to aliasing.

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion

PubMed Central

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-01-01

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy. PMID:26334278

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion.

PubMed

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-08-31

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy.

A Novel Approach for Adaptive Signal Processing

NASA Technical Reports Server (NTRS)

Chen, Ya-Chin; Juang, Jer-Nan

1998-01-01

Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

Fundamentals of image acquisition and processing in the digital era.

PubMed

Farman, A G

2003-01-01

To review the historic context for digital imaging in dentistry and to outline the fundamental issues related to digital imaging modalities. Digital dental X-ray images can be achieved by scanning analog film radiographs (secondary capture), with photostimulable phosphors, or using solid-state detectors (e.g. charge-coupled device and complementary metal oxide semiconductor). There are four characteristics that are basic to all digital image detectors; namely, size of active area, signal-to-noise ratio, contrast resolution and the spatial resolution. To perceive structure in a radiographic image, there needs to be sufficient difference between contrasting densities. This primarily depends on the differences in the attenuation of the X-ray beam by adjacent tissues. It is also depends on the signal received; therefore, contrast tends to increase with increased exposure. Given adequate signal and sufficient differences in radiodensity, contrast will be sufficient to differentiate between adjacent structures, irrespective of the recording modality and processing used. Where contrast is not sufficient, digital images can sometimes be post-processed to disclose details that would otherwise go undetected. For example, cephalogram isodensity mapping can improve soft tissue detail. It is concluded that it could be a further decade or two before three-dimensional digital imaging systems entirely replace two-dimensional analog films. Such systems need not only to produce prettier images, but also to provide a demonstrable evidence-based higher standard of care at a cost that is not economically prohibitive for the practitioner or society, and which allows efficient and effective workflow within the business of dental practice.

Spontaneous Raman Scattering Diagnostics: Applications in Practical Combustion Systems. Chapter 5

NASA Technical Reports Server (NTRS)

Kojima, Jun; Viet-Nguyen, Quang; Lackner, Maximilian (Editor); Winter, Franz (Editor); Agarwal, Avinash (Editor)

2010-01-01

In this chapter, the recent advancements and practical aspects of laser SRS diagnostics have been reviewed wi til regards to applications in practical combustion systems. Clearly, SRS represents a theoretically and experimentally mature diagnostic technology that has become an essential tool for multiscalar measurements in turbulent combustion at elevated pressures. Today, time-, space-, spectrally, and even polarization-resolved S RS diagnostics is at hand, with aid from recent innovations in theoretical and technological developments on electro-optical or electromechanical devices. Whilst a linear increase in SRS signals can be expected in high-pressure systems (this is perhaps one of the most important advantages for using SRS in high-pressure systems), there are practical (often severe) restrictions associated with pressurized vessels, due mainly to the limited degree of optical access. This narrows ti,e available choice of diagnostics that can be employed at any given time. Point-wise SRS diagnostics provides the highest accuracy on the chemical species and temperature measurements, and will continue to remain a vital approach for the study in such harsh environments. The practical design considerations and hands-on set-up guide for SRS diagnostics provided in this chapter are rarely presented elsewhere. Although the second-harmonic Nd:YAG pulsed laser (532 nm), combined with pulse-stretching optics or the recently introduced White Cell-based laser, seems to be the most favored excitation source of choice by the research community, UV excitation will undoubtedly continue to be used on many occasions, and especially in sooting flames. Detection methods may be divided into ICCD-based nanosecond-gate detection or a rotary-chopper electromechanical shutter-based CCD array detection, and the levels of background flame emission in individual cases would determine this critical design choice. Here, a process of Raman signal calibration based on ti,e crosstalk matrix formalism was explained step-by-step. As tI,is process may be very time-consuming and expensive, a well-planned experimental approach (01' building a transferable calibration database or library (at least with in a user's own facility over a series of different testing and runs) is vitally important. Hands on advice on the design and construction of flow control systems for high pressure burner facilities were also presented.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

Informational approach to the analysis of acoustic signals

NASA Astrophysics Data System (ADS)

Senkevich, Yuriy; Dyuk, Vyacheslav; Mishchenko, Mikhail; Solodchuk, Alexandra

2017-10-01

The example of linguistic processing of acoustic signals of a seismic event would be an information approach to the processing of non-stationary signals. The method for converting an acoustic signal into an information message is described by identifying repetitive self-similar patterns. The definitions of the event selection indicators in the symbolic recording of the acoustic signal are given. The results of processing an acoustic signal by a computer program realizing the processing of linguistic data are shown. Advantages and disadvantages of using software algorithms are indicated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polese, Luigi Gentile; Brackney, Larry

An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generatesmore » an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.« less

Extremely Coherent Microwave Emission from Spin Torque Oscillator Stabilized by Phase Locked Loop

PubMed Central

Tamaru, Shingo; Kubota, Hitoshi; Yakushiji, Kay; Yuasa, Shinji; Fukushima, Akio

2015-01-01

Spin torque oscillator (STO) has been attracting a great deal of attention as a candidate for the next generation microwave signal sources for various modern electronics systems since its advent. However, the phase noise of STOs under free running oscillation is still too large to be used in practical microwave applications, thus an industrially viable means to stabilize its oscillation has been strongly sought. Here we demonstrate implementation of a phase locked loop using a STO as a voltage controlled oscillator (VCO) that generates a 7.344 GHz microwave signal stabilized by a 153 MHz reference signal. Spectrum measurement showed successful phase locking of the microwave signal to the reference signal, characterized by an extremely narrow oscillation peak with a linewidth of less than the measurement limit of 1 Hz. This demonstration should be a major breakthrough toward various practical applications of STOs. PMID:26658880

Worry spreads: interpersonal transfer of problem-related anxiety.

PubMed

Parkinson, Brian; Simons, Gwenda

2012-01-01

This paper distinguishes processes potentially contributing to interpersonal anxiety transfer, including object-directed social appraisal, empathic worry, and anxiety contagion, and reviews evidence for their operation. We argue that these anxiety-transfer processes may be exploited strategically when attempting to regulate relationship partners' emotion. More generally, anxiety may serve as either a warning signal to other people about threat (alerting function) or an appeal for emotional support or practical help (comfort-seeking function). Tensions between these two interpersonal functions may account for mutually incongruent interpersonal responses to expressed anxiety, including mistargeted interpersonal regulation attempts. Because worry waxes and wanes over time as a function of other people's ongoing reactions, interpersonal interventions may help to alleviate some of its maladaptive consequences.

A robust approach to measuring the detective quantum efficiency of radiographic detectors in a clinical setting

NASA Astrophysics Data System (ADS)

McDonald, Michael C.; Kim, H. K.; Henry, J. R.; Cunningham, I. A.

2012-03-01

The detective quantum efficiency (DQE) is widely accepted as a primary measure of x-ray detector performance in the scientific community. A standard method for measuring the DQE, based on IEC 62220-1, requires the system to have a linear response meaning that the detector output signals are proportional to the incident x-ray exposure. However, many systems have a non-linear response due to characteristics of the detector, or post processing of the detector signals, that cannot be disabled and may involve unknown algorithms considered proprietary by the manufacturer. For these reasons, the DQE has not been considered as a practical candidate for routine quality assurance testing in a clinical setting. In this article we described a method that can be used to measure the DQE of both linear and non-linear systems that employ only linear image processing algorithms. The method was validated on a Cesium Iodide based flat panel system that simultaneously stores a raw (linear) and processed (non-linear) image for each exposure. It was found that the resulting DQE was equivalent to a conventional standards-compliant DQE with measurement precision, and the gray-scale inversion and linear edge enhancement did not affect the DQE result. While not IEC 62220-1 compliant, it may be adequate for QA programs.

Improving Drive Files for Vehicle Road Simulations

NASA Astrophysics Data System (ADS)

Cherng, John G.; Goktan, Ali; French, Mark; Gu, Yi; Jacob, Anil

2001-09-01

Shaker tables are commonly used in laboratories for automotive vehicle component testing to study durability and acoustics performance. An example is development testing of car seats. However, it is difficult to repeat the measured road data perfectly with the response of a shaker table as there are basic differences in dynamic characteristics between a flexible vehicle and substantially rigid shaker table. In addition, there are performance limits in the shaker table drive systems that can limit correlation. In practice, an optimal drive signal for the actuators is created iteratively. During each iteration, the error between the road data and the response data is minimised by an optimising algorithm which is generally a part of the feed back loop of the shake table controller. This study presents a systematic investigation to the errors in time and frequency domains as well as joint time-frequency domain and an evaluation of different digital signal processing techniques that have been used in previous work. In addition, we present an innovative approach that integrates the dynamic characteristics of car seats and the human body into the error-minimising iteration process. We found that the iteration process can be shortened and the error reduced by using a weighting function created by normalising the frequency response function of the car seat. Two road data test sets were used in the study.

The Application of Coherent Local Time for Optical Time Transfer and the Quantification of Systematic Errors in Satellite Laser Ranging

NASA Astrophysics Data System (ADS)

Schreiber, K. Ulrich; Kodet, Jan

2018-02-01

Highly precise time and stable reference frequencies are fundamental requirements for space geodesy. Satellite laser ranging (SLR) is one of these techniques, which differs from all other applications like Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS) and finally Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) by the fact that it is an optical two-way measurement technique. That means that there is no need for a clock synchronization process between both ends of the distance covered by the measurement technique. Under the assumption of isotropy for the speed of light, SLR establishes the only practical realization of the Einstein Synchronization process so far. Therefore it is a powerful time transfer technique. However, in order to transfer time between two remote clocks, it is also necessary to tightly control all possible signal delays in the ranging process. This paper discusses the role of time and frequency in SLR as well as the error sources before it address the transfer of time between ground and space. The need of an improved signal delay control led to a major redesign of the local time and frequency distribution at the Geodetic Observatory Wettzell. Closure measurements can now be used to identify and remove systematic errors in SLR measurements.

Rapid Biochemical Mixture Screening by Three-Dimensional Patterned Multifunctional Substrate with Ultra-Thin Layer Chromatography (UTLC) and Surface Enhanced Raman Scattering (SERS).

PubMed

Lee, Bi-Shen; Lin, Pi-Chen; Lin, Ding-Zheng; Yen, Ta-Jen

2018-01-11

We present a three-dimensional patterned (3DP) multifunctional substrate with the functions of ultra-thin layer chromatography (UTLC) and surface enhanced Raman scattering (SERS), which simultaneously enables mixture separation, target localization and label-free detection. This multifunctional substrate is comprised of a 3DP silicon nanowires array (3DP-SiNWA), decorated with silver nano-dendrites (AgNDs) atop. The 3DP-SiNWA is fabricated by a facile photolithographic process and low-cost metal assisted chemical etching (MaCE) process. Then, the AgNDs are decorated onto 3DP-SiNWA by a wet chemical reduction process, obtaining 3DP-AgNDs@SiNWA multifunctional substrates. With various patterns designed on the substrates, the signal intensity could be maximized by the excellent confinement and concentrated effects of patterns. By using this 3DP-AgNDs@SiNWA substrate to scrutinize the mixture of two visible dyes, the individual target could be recognized and further boosted the Raman signal of target 15.42 times comparing to the un-patterned AgNDs@SiNWA substrate. Therefore, such a three-dimensional patterned multifunctional substrate empowers rapid mixture screening, and can be readily employed in practical applications for biochemical assays, food safety and other fields.

Comparison of Foam-Based and Spring-Loaded Dry EEG Electrodes with Wet Electrodes in Resting and Moving Conditions*

PubMed Central

Yeung, Arnold; Garudadri, Harinath; Van Toen, Carolyn; Mercier, Patrick; Balkan, Ozgur; Makeig, Scott; Virji-Babul, Naznin

2018-01-01

The introduction of dry electrodes for EEG measurements has opened up possibilities of recording EEG outside of standard clinical environments by reducing required preparation and maintenance. However, the signal quality of dry electrodes in comparison with wet electrodes has not yet been evaluated under activities of daily life (ADL) or high motion tasks. In this study, we compared the performances of foam-based and spring-loaded dry electrodes with wet electrodes under three different task conditions: resting state, walking, and cycling. Our analysis showed signals obtained by the 2 types of dry electrodes and obtained by wet electrodes displayed high correlation for all conditions, while being prone to similar environmental and electrode-based artifacts. Overall, our results suggest that dry electrodes have a similar signal quality in comparison to wet electrodes and may be more practical for use in mobile and real-time motion applications due to their convenience. In addition, we conclude that as with wet electrodes, post-processing can mitigate motion artifacts in ambulatory EEG acquisition. PMID:26737936

Ligand-Induced Dynamics of Neurotrophin Receptors Investigated by Single-Molecule Imaging Approaches

PubMed Central

Marchetti, Laura; Luin, Stefano; Bonsignore, Fulvio; de Nadai, Teresa; Beltram, Fabio; Cattaneo, Antonino

2015-01-01

Neurotrophins are secreted proteins that regulate neuronal development and survival, as well as maintenance and plasticity of the adult nervous system. The biological activity of neurotrophins stems from their binding to two membrane receptor types, the tropomyosin receptor kinase and the p75 neurotrophin receptors (NRs). The intracellular signalling cascades thereby activated have been extensively investigated. Nevertheless, a comprehensive description of the ligand-induced nanoscale details of NRs dynamics and interactions spanning from the initial lateral movements triggered at the plasma membrane to the internalization and transport processes is still missing. Recent advances in high spatio-temporal resolution imaging techniques have yielded new insight on the dynamics of NRs upon ligand binding. Here we discuss requirements, potential and practical implementation of these novel approaches for the study of neurotrophin trafficking and signalling, in the framework of current knowledge available also for other ligand-receptor systems. We shall especially highlight the correlation between the receptor dynamics activated by different neurotrophins and the respective signalling outcome, as recently revealed by single-molecule tracking of NRs in living neuronal cells. PMID:25603178

A Sensitive Electrochemical Immunosensor Based on PAMAM Dendrimer-Encapsulated Au for Detection of Norfloxacin in Animal-Derived Foods.

PubMed

Liu, Bing; Li, Min; Zhao, Yaoshuai; Pan, Mingfei; Gu, Ying; Sheng, Wei; Fang, Guozhen; Wang, Shuo

2018-06-15

In this work, a sensitive electrochemical immunosensor has been reported for the determination of norfloxacin in animal-derived foods. The poly (amidoamine) dendrimer encapsulated gold nanoparticles (PAMAM-Au) played dual roles in the proposed sensing platform which not only accelerated the electron transfer process of sensing, but also increased the efficiency of the immobilized antibody. The HRP-labeled antigen, as the signal labels in the immunosensor, was introduced to catalyze the following reaction of the substrate hydroquinone with the aid of H₂O₂ in the competitive reaction. On the basis of the signal amplification of PAMAM-Au, the signal intensity was linearly related to the concentration of norfloxacin in the range of 1 μg·L −1 ⁻10 mg·L −1 . All the results showed that the proposed strategy with low LOD (0.3837 μg·L −1 ) and favorable recovery (91.6⁻106.1%) in the practical sample, and it could provide a suitable protocol for norfloxacin detection in animal-derived foods with high sensitivity, good accuracy, and stability.

BPSK Demodulation Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Garcia, Thomas R.

1996-01-01

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

Detection of BCG bacteria using a magnetoresistive biosensor: A step towards a fully electronic platform for tuberculosis point-of-care detection.

PubMed

Barroso, Teresa G; Martins, Rui C; Fernandes, Elisabete; Cardoso, Susana; Rivas, José; Freitas, Paulo P

2018-02-15

Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 10 4 cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; iii) application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03log 10 (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used. Copyright © 2017 Elsevier B.V. All rights reserved.

Gas turbine engine control system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Idelchik, M.S.

1991-02-19

This paper describes a method for controlling a gas turbine engine. It includes receiving an error signal and processing the error signal to form a primary control signal; receiving at least one anticipatory demand signal and processing the signal to form an anticipatory fuel control signal.

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Scatter correction for x-ray conebeam CT using one-dimensional primary modulation

NASA Astrophysics Data System (ADS)

Zhu, Lei; Gao, Hewei; Bennett, N. Robert; Xing, Lei; Fahrig, Rebecca

2009-02-01

Recently, we developed an efficient scatter correction method for x-ray imaging using primary modulation. A two-dimensional (2D) primary modulator with spatially variant attenuating materials is inserted between the x-ray source and the object to separate primary and scatter signals in the Fourier domain. Due to the high modulation frequency in both directions, the 2D primary modulator has a strong scatter correction capability for objects with arbitrary geometries. However, signal processing on the modulated projection data requires knowledge of the modulator position and attenuation. In practical systems, mainly due to system gantry vibration, beam hardening effects and the ramp-filtering in the reconstruction, the insertion of the 2D primary modulator results in artifacts such as rings in the CT images, if no post-processing is applied. In this work, we eliminate the source of artifacts in the primary modulation method by using a one-dimensional (1D) modulator. The modulator is aligned parallel to the ramp-filtering direction to avoid error magnification, while sufficient primary modulation is still achieved for scatter correction on a quasicylindrical object, such as a human body. The scatter correction algorithm is also greatly simplified for the convenience and stability in practical implementations. The method is evaluated on a clinical CBCT system using the Catphan© 600 phantom. The result shows effective scatter suppression without introducing additional artifacts. In the selected regions of interest, the reconstruction error is reduced from 187.2HU to 10.0HU if the proposed method is used.

49 CFR 218.29 - Alternate methods of protection.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.29 Alternate methods of protection. Instead of providing blue signal protection for workers in accordance with § 218.27, the following methods for blue signal protection may be used: (a) When workers are...

49 CFR 218.29 - Alternate methods of protection.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.29 Alternate methods of protection. Instead of providing blue signal protection for workers in accordance with § 218.27, the following methods for blue signal protection may be used: (a) When workers are...

49 CFR 218.29 - Alternate methods of protection.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.29 Alternate methods of protection. Instead of providing blue signal protection for workers in accordance with § 218.27, the following methods for blue signal protection may be used: (a) When workers are...

49 CFR 218.29 - Alternate methods of protection.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.29 Alternate methods of protection. Instead of providing blue signal protection for workers in accordance with § 218.27, the following methods for blue signal protection may be used: (a) When workers are...

Decoupling feedforward and feedback structures in hybrid active noise control systems for uncorrelated narrowband disturbances

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Burnett, Ian S.; Guo, Yecai

2015-08-01

Hybrid feedforward and feedback structures are useful for active noise control (ANC) applications where the noise can only be partially obtained with reference sensors. The traditional method uses the secondary signals of both the feedforward and feedback structures to synthesize a reference signal for the feedback structure in the hybrid structure. However, this approach introduces coupling between the feedforward and feedback structures and parameter changes in one structure affect the other during adaptation such that the feedforward and feedback structures must be optimized simultaneously in practical ANC system design. Two methods are investigated in this paper to remove such coupling effects. One is a simplified method, which uses the error signal directly as the reference signal in the feedback structure, and the second method generates the reference signal for the feedback structure by using only the secondary signal from the feedback structure and utilizes the generated reference signal as the error signal of the feedforward structure. Because the two decoupling methods can optimize the feedforward and feedback structures separately, they provide more flexibility in the design and optimization of the adaptive filters in practical ANC applications.

Research on the fault diagnosis of bearing based on wavelet and demodulation

NASA Astrophysics Data System (ADS)

Li, Jiapeng; Yuan, Yu

2017-05-01

As a most commonly-used machine part, antifriction bearing is extensively used in mechanical equipment. Vibration signal analysis is one of the methods to monitor and diagnose the running status of antifriction bearings. Therefore, using wavelet analysis for demising is of great importance in the engineering practice. This paper firstly presented the basic theory of wavelet analysis to study the transformation, decomposition and reconstruction of wavelet. In addition, edition software LabVIEW was adopted to conduct wavelet and demodulation upon the vibration signal of antifriction bearing collected. With the combination of Hilbert envelop demodulation analysis, the fault character frequencies of the demised signal were extracted to conduct fault diagnosis analysis, which serves as a reference for the wavelet and demodulation of the vibration signal in engineering practice.

Servo Platform Circuit Design of Pendulous Gyroscope Based on DSP

NASA Astrophysics Data System (ADS)

Tan, Lilong; Wang, Pengcheng; Zhong, Qiyuan; Zhang, Cui; Liu, Yunfei

2018-03-01

In order to solve the problem when a certain type of pendulous gyroscope in the initial installation deviation more than 40 degrees, that the servo platform can not be up to the speed of the gyroscope in the rough north seeking phase. This paper takes the digital signal processor TMS320F28027 as the core, uses incremental digital PID algorithm, carries out the circuit design of the servo platform. Firstly, the hardware circuit is divided into three parts: DSP minimum system, motor driving circuit and signal processing circuit, then the mathematical model of incremental digital PID algorithm is established, based on the model, writes the PID control program in CCS3.3, finally, the servo motor tracking control experiment is carried out, it shows that the design can significantly improve the tracking ability of the servo platform, and the design has good engineering practice.

Practical considerations of image analysis and quantification of signal transduction IHC staining.

PubMed

Grunkin, Michael; Raundahl, Jakob; Foged, Niels T

2011-01-01

The dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations. However, immunohistochemistry is a multistep procedure including a lot of technical pitfalls leading to intra- and interlaboratory variability of its outcome. The resulting variations in staining intensity and disruption of original morphology are an extra challenge for the image analysis software, which therefore preferably should be dedicated to the detection and quantification of histomorphometrical end points.

Graphene radio frequency receiver integrated circuit.

PubMed

Han, Shu-Jen; Garcia, Alberto Valdes; Oida, Satoshi; Jenkins, Keith A; Haensch, Wilfried

2014-01-01

Graphene has attracted much interest as a future channel material in radio frequency electronics because of its superior electrical properties. Fabrication of a graphene integrated circuit without significantly degrading transistor performance has proven to be challenging, posing one of the major bottlenecks to compete with existing technologies. Here we present a fabrication method fully preserving graphene transistor quality, demonstrated with the implementation of a high-performance three-stage graphene integrated circuit. The circuit operates as a radio frequency receiver performing signal amplification, filtering and downconversion mixing. All circuit components are integrated into 0.6 mm(2) area and fabricated on 200 mm silicon wafers, showing the unprecedented graphene circuit complexity and silicon complementary metal-oxide-semiconductor process compatibility. The demonstrated circuit performance allow us to use graphene integrated circuit to perform practical wireless communication functions, receiving and restoring digital text transmitted on a 4.3-GHz carrier signal.

Note: An improved calibration system with phase correction for electronic transformers with digital output.

PubMed

Cheng, Han-miao; Li, Hong-bin

2015-08-01

The existing electronic transformer calibration systems employing data acquisition cards cannot satisfy some practical applications, because the calibration systems have phase measurement errors when they work in the mode of receiving external synchronization signals. This paper proposes an improved calibration system scheme with phase correction to improve the phase measurement accuracy. We employ NI PCI-4474 to design a calibration system, and the system has the potential to receive external synchronization signals and reach extremely high accuracy classes. Accuracy verification has been carried out in the China Electric Power Research Institute, and results demonstrate that the system surpasses the accuracy class 0.05. Furthermore, this system has been used to test the harmonics measurement accuracy of all-fiber optical current transformers. In the same process, we have used an existing calibration system, and a comparison of the test results is presented. The system after improvement is suitable for the intended applications.

Effect of driving voltage polarity on dynamic response characteristics of electrowetting liquid lens

NASA Astrophysics Data System (ADS)

Na, Xie; Ning, Zhang; Rong-Qing, Xu

2018-05-01

A test device is developed for studying the dynamic process of an electrowetting liquid lens. By analyzing the light signals through the liquid lens, the dynamical properties of the lens are investigated. In our experiment, three types of pulse, i.e., sine, bipolar pulse, and single pulse signals, are employed to drive the liquid lens, and the dynamic characteristics of the lens are subsequently analyzed. The results show that the positive and negative polarities of the driving voltage can cause a significant difference in the response of the liquid lens; meanwhile, the lens’s response to the negative polarity of the driving voltage is clearer. We use the theory of charge restraint to explain this phenomenon, and it is concluded that the negative ions are more easily restrained by a dielectric layer. This work gives direct guidance for practical applications based on an electrowetting liquid lens.

Feasibility study for future implantable neural-silicon interface devices.

PubMed

Al-Armaghany, Allann; Yu, Bo; Mak, Terrence; Tong, Kin-Fai; Sun, Yihe

2011-01-01

The emerging neural-silicon interface devices bridge nerve systems with artificial systems and play a key role in neuro-prostheses and neuro-rehabilitation applications. Integrating neural signal collection, processing and transmission on a single device will make clinical applications more practical and feasible. This paper focuses on the wireless antenna part and real-time neural signal analysis part of implantable brain-machine interface (BMI) devices. We propose to use millimeter-wave for wireless connections between different areas of a brain. Various antenna, including microstrip patch, monopole antenna and substrate integrated waveguide antenna are considered for the intra-cortical proximity communication. A Hebbian eigenfilter based method is proposed for multi-channel neuronal spike sorting. Folding and parallel design techniques are employed to explore various structures and make a trade-off between area and power consumption. Field programmable logic arrays (FPGAs) are used to evaluate various structures.

Study on data acquisition system based on reconfigurable cache technology

NASA Astrophysics Data System (ADS)

Zhang, Qinchuan; Li, Min; Jiang, Jun

2018-03-01

Waveform capture rate is one of the key features of digital acquisition systems, which represents the waveform processing capability of the system in a unit time. The higher the waveform capture rate is, the larger the chance to capture elusive events is and the more reliable the test result is. First, this paper analyzes the impact of several factors on the waveform capture rate of the system, then the novel technology based on reconfigurable cache is further proposed to optimize system architecture, and the simulation results show that the signal-to-noise ratio of signal, capacity, and structure of cache have significant effects on the waveform capture rate. Finally, the technology is demonstrated by the engineering practice, and the results show that the waveform capture rate of the system is improved substantially without significant increase of system's cost, and the technology proposed has a broad application prospect.

Sparse Bayesian learning for DOA estimation with mutual coupling.

PubMed

Dai, Jisheng; Hu, Nan; Xu, Weichao; Chang, Chunqi

2015-10-16

Sparse Bayesian learning (SBL) has given renewed interest to the problem of direction-of-arrival (DOA) estimation. It is generally assumed that the measurement matrix in SBL is precisely known. Unfortunately, this assumption may be invalid in practice due to the imperfect manifold caused by unknown or misspecified mutual coupling. This paper describes a modified SBL method for joint estimation of DOAs and mutual coupling coefficients with uniform linear arrays (ULAs). Unlike the existing method that only uses stationary priors, our new approach utilizes a hierarchical form of the Student t prior to enforce the sparsity of the unknown signal more heavily. We also provide a distinct Bayesian inference for the expectation-maximization (EM) algorithm, which can update the mutual coupling coefficients more efficiently. Another difference is that our method uses an additional singular value decomposition (SVD) to reduce the computational complexity of the signal reconstruction process and the sensitivity to the measurement noise.

Sparse Reconstruction of Regional Gravity Signal Based on Stabilized Orthogonal Matching Pursuit (SOMP)

NASA Astrophysics Data System (ADS)

Saadat, S. A.; Safari, A.; Needell, D.

2016-06-01

The main role of gravity field recovery is the study of dynamic processes in the interior of the Earth especially in exploration geophysics. In this paper, the Stabilized Orthogonal Matching Pursuit (SOMP) algorithm is introduced for sparse reconstruction of regional gravity signals of the Earth. In practical applications, ill-posed problems may be encountered regarding unknown parameters that are sensitive to the data perturbations. Therefore, an appropriate regularization method needs to be applied to find a stabilized solution. The SOMP algorithm aims to regularize the norm of the solution vector, while also minimizing the norm of the corresponding residual vector. In this procedure, a convergence point of the algorithm that specifies optimal sparsity-level of the problem is determined. The results show that the SOMP algorithm finds the stabilized solution for the ill-posed problem at the optimal sparsity-level, improving upon existing sparsity based approaches.

Recommendations for the standardization and interpretation of the electrocardiogram: part I: the electrocardiogram and its technology a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society endorsed by the International Society for Computerized Electrocardiology.

PubMed

Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S; Josephson, Mark; Mason, Jay W; Okin, Peter; Surawicz, Borys; Wellens, Hein

2007-03-13

This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.

Recommendations for the standardization and interpretation of the electrocardiogram: part I: The electrocardiogram and its technology: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society: endorsed by the International Society for Computerized Electrocardiology.

PubMed

Kligfield, Paul; Gettes, Leonard S; Bailey, James J; Childers, Rory; Deal, Barbara J; Hancock, E William; van Herpen, Gerard; Kors, Jan A; Macfarlane, Peter; Mirvis, David M; Pahlm, Olle; Rautaharju, Pentti; Wagner, Galen S; Josephson, Mark; Mason, Jay W; Okin, Peter; Surawicz, Borys; Wellens, Hein

2007-03-13

This statement examines the relation of the resting ECG to its technology. Its purpose is to foster understanding of how the modern ECG is derived and displayed and to establish standards that will improve the accuracy and usefulness of the ECG in practice. Derivation of representative waveforms and measurements based on global intervals are described. Special emphasis is placed on digital signal acquisition and computer-based signal processing, which provide automated measurements that lead to computer-generated diagnostic statements. Lead placement, recording methods, and waveform presentation are reviewed. Throughout the statement, recommendations for ECG standards are placed in context of the clinical implications of evolving ECG technology.

Correlation of surface site formation to nanoisland growth in the electrochemical roughening of Pt(111)

NASA Astrophysics Data System (ADS)

Jacobse, Leon; Huang, Yi-Fan; Koper, Marc T. M.; Rost, Marcel J.

2018-03-01

Platinum plays a central role in a variety of electrochemical devices and its practical use depends on the prevention of electrode degradation. However, understanding the underlying atomic processes under conditions of repeated oxidation and reduction inducing irreversible surface structure changes has proved challenging. Here, we examine the correlation between the evolution of the electrochemical signal of Pt(111) and its surface roughening by simultaneously performing cyclic voltammetry and in situ electrochemical scanning tunnelling microscopy (EC-STM). We identify a `nucleation and early growth' regime of nanoisland formation, and a `late growth' regime after island coalescence, which continues up to at least 170 cycles. The correlation analysis shows that each step site that is created in the `late growth' regime contributes equally strongly to both the electrochemical and the roughness evolution. In contrast, in the `nucleation and early growth' regime, created step sites contribute to the roughness, but not to the electrochemical signal.

[Analysis of several key problems of good agricultural practice (GAP) of Chinese materia medica].

PubMed

Yang, Guang; Guo, Lan-Ping; Zhou, Xiu-Teng; Huang, Lu-Qi

2016-04-01

This paper reviewed the historical background of the GAP, analyzed the development experience of five Ps (GMP, GLP, GSP, GCP, GAP), analyzed the GAP based on economic theories, and pointed out that the core problem of GAP is ignoring economic laws. Once the GAP, is a process of certification, but neither the GAP announcement could be transformed into signal transmission quality in the product market, nor consumers could recognize the difference between GAP and non-GAP herbs in the terminal market, so manufacturers lack motivation for GAP certification. In this paper, we pointed out, that the GAP certification system should be redesigned under the guidance of economics, third party certification body, supervised by drug administration organization, to certificate GAP as high quality standards, to improve signal transduction mechanism of GAP certification, and to integrate GAP with the market. Copyright© by the Chinese Pharmaceutical Association.

Graphene radio frequency receiver integrated circuit

NASA Astrophysics Data System (ADS)

Han, Shu-Jen; Garcia, Alberto Valdes; Oida, Satoshi; Jenkins, Keith A.; Haensch, Wilfried

2014-01-01

Graphene has attracted much interest as a future channel material in radio frequency electronics because of its superior electrical properties. Fabrication of a graphene integrated circuit without significantly degrading transistor performance has proven to be challenging, posing one of the major bottlenecks to compete with existing technologies. Here we present a fabrication method fully preserving graphene transistor quality, demonstrated with the implementation of a high-performance three-stage graphene integrated circuit. The circuit operates as a radio frequency receiver performing signal amplification, filtering and downconversion mixing. All circuit components are integrated into 0.6 mm2 area and fabricated on 200 mm silicon wafers, showing the unprecedented graphene circuit complexity and silicon complementary metal-oxide-semiconductor process compatibility. The demonstrated circuit performance allow us to use graphene integrated circuit to perform practical wireless communication functions, receiving and restoring digital text transmitted on a 4.3-GHz carrier signal.

Investigation of optical current transformer signal processing method based on an improved Kalman algorithm

NASA Astrophysics Data System (ADS)

Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan

2018-01-01

This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

A non-uniformly under-sampled blade tip-timing signal reconstruction method for blade vibration monitoring.

PubMed

Hu, Zheng; Lin, Jun; Chen, Zhong-Sheng; Yang, Yong-Min; Li, Xue-Jun

2015-01-22

High-speed blades are often prone to fatigue due to severe blade vibrations. In particular, synchronous vibrations can cause irreversible damages to the blade. Blade tip-timing methods (BTT) have become a promising way to monitor blade vibrations. However, synchronous vibrations are unsuitably monitored by uniform BTT sampling. Therefore, non-equally mounted probes have been used, which will result in the non-uniformity of the sampling signal. Since under-sampling is an intrinsic drawback of BTT methods, how to analyze non-uniformly under-sampled BTT signals is a big challenge. In this paper, a novel reconstruction method for non-uniformly under-sampled BTT data is presented. The method is based on the periodically non-uniform sampling theorem. Firstly, a mathematical model of a non-uniform BTT sampling process is built. It can be treated as the sum of certain uniform sample streams. For each stream, an interpolating function is required to prevent aliasing in the reconstructed signal. Secondly, simultaneous equations of all interpolating functions in each sub-band are built and corresponding solutions are ultimately derived to remove unwanted replicas of the original signal caused by the sampling, which may overlay the original signal. In the end, numerical simulations and experiments are carried out to validate the feasibility of the proposed method. The results demonstrate the accuracy of the reconstructed signal depends on the sampling frequency, the blade vibration frequency, the blade vibration bandwidth, the probe static offset and the number of samples. In practice, both types of blade vibration signals can be particularly reconstructed by non-uniform BTT data acquired from only two probes.

A Non-Uniformly Under-Sampled Blade Tip-Timing Signal Reconstruction Method for Blade Vibration Monitoring

PubMed Central

Hu, Zheng; Lin, Jun; Chen, Zhong-Sheng; Yang, Yong-Min; Li, Xue-Jun

2015-01-01

High-speed blades are often prone to fatigue due to severe blade vibrations. In particular, synchronous vibrations can cause irreversible damages to the blade. Blade tip-timing methods (BTT) have become a promising way to monitor blade vibrations. However, synchronous vibrations are unsuitably monitored by uniform BTT sampling. Therefore, non-equally mounted probes have been used, which will result in the non-uniformity of the sampling signal. Since under-sampling is an intrinsic drawback of BTT methods, how to analyze non-uniformly under-sampled BTT signals is a big challenge. In this paper, a novel reconstruction method for non-uniformly under-sampled BTT data is presented. The method is based on the periodically non-uniform sampling theorem. Firstly, a mathematical model of a non-uniform BTT sampling process is built. It can be treated as the sum of certain uniform sample streams. For each stream, an interpolating function is required to prevent aliasing in the reconstructed signal. Secondly, simultaneous equations of all interpolating functions in each sub-band are built and corresponding solutions are ultimately derived to remove unwanted replicas of the original signal caused by the sampling, which may overlay the original signal. In the end, numerical simulations and experiments are carried out to validate the feasibility of the proposed method. The results demonstrate the accuracy of the reconstructed signal depends on the sampling frequency, the blade vibration frequency, the blade vibration bandwidth, the probe static offset and the number of samples. In practice, both types of blade vibration signals can be particularly reconstructed by non-uniform BTT data acquired from only two probes. PMID:25621612

40-Gbps optical backbone network deep packet inspection based on FPGA

NASA Astrophysics Data System (ADS)

Zuo, Yuan; Huang, Zhiping; Su, Shaojing

2014-11-01

In the era of information, the big data, which contains huge information, brings about some problems, such as high speed transmission, storage and real-time analysis and process. As the important media for data transmission, the Internet is the significant part for big data processing research. With the large-scale usage of the Internet, the data streaming of network is increasing rapidly. The speed level in the main fiber optic communication of the present has reached 40Gbps, even 100Gbps, therefore data on the optical backbone network shows some features of massive data. Generally, data services are provided via IP packets on the optical backbone network, which is constituted with SDH (Synchronous Digital Hierarchy). Hence this method that IP packets are directly mapped into SDH payload is named POS (Packet over SDH) technology. Aiming at the problems of real time process of high speed massive data, this paper designs a process system platform based on ATCA for 40Gbps POS signal data stream recognition and packet content capture, which employs the FPGA as the CPU. This platform offers pre-processing of clustering algorithms, service traffic identification and data mining for the following big data storage and analysis with high efficiency. Also, the operational procedure is proposed in this paper. Four channels of 10Gbps POS signal decomposed by the analysis module, which chooses FPGA as the kernel, are inputted to the flow classification module and the pattern matching component based on TCAM. Based on the properties of the length of payload and net flows, buffer management is added to the platform to keep the key flow information. According to data stream analysis, DPI (deep packet inspection) and flow balance distribute, the signal is transmitted to the backend machine through the giga Ethernet ports on back board. Practice shows that the proposed platform is superior to the traditional applications based on ASIC and NP.

Exploring the Potential Routine Use of Electronic Healthcare Record Data to Strengthen Early Signal Assessment in UK Medicines Regulation: Proof-of-Concept Study.

PubMed

Donegan, Katherine; Owen, Rebecca; Bird, Helena; Burch, Brian; Smith, Alex; Tregunno, Phil

2018-05-03

Electronic healthcare record (EHR) databases are used within pharmacoepidemiology studies to confirm or refute safety signals arising from spontaneous adverse event reports. However, there has been limited routine use of such data earlier in the signal management process, to help rapidly contextualise signals and strengthen preliminary assessment or to inform decisions regarding action including the need for further studies. This study explores the value of EHR used in this way within a regulatory environment via an automated analysis platform. Safety signals raised at the UK Medicines and Healthcare products Regulatory Agency (MHRA) between July 2014 and June 2015 were individually reviewed by a multi-disciplinary team. They assessed the feasibility of identifying the exposure and event of interest using primary care data from the Clinical Practice Research Datalink (CPRD) within the Commonwealth Vigilance Workbench (CVW) Longitudinal Module platform, which was designed to facilitate routine descriptive analysis of signals using EHR. Three signals, where exposure and event could be well identified, were retrospectively analysed using the platform. Of 69 unique new signals, 20 were for drugs prescribed predominately in secondary care or available without prescription, which would not be identified in primary care. A further 17 were brand, formulation, or dose-specific issues, were related to mortality, were relevant only to a subgroup of patients, or were drug interactions, and hence could not be reviewed using the platform given its limitations. Analyses of exposure and incidence of the adverse event could be produced using CPRD within the CMV Longitudinal Module for 32 (46%) signals. The case studies demonstrated that the data provided supporting evidence for confirming initial assessment of the signal and deciding upon the need for further action. CPRD can routinely provide useful early insights into clinical context when assessing a large proportion of safety signals within a regulatory environment provided that a flexible approach is adopted within the analysis platform.

K-mean clustering algorithm for processing signals from compound semiconductor detectors

NASA Astrophysics Data System (ADS)

Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo

2011-12-01

The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.

Signal processing in ultrasound. [for diagnostic medicine

NASA Technical Reports Server (NTRS)

Le Croissette, D. H.; Gammell, P. M.

1978-01-01

Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

Theoretical detection threshold of the proton-acoustic range verification technique.

PubMed

Ahmad, Moiz; Xiang, Liangzhong; Yousefi, Siavash; Xing, Lei

2015-10-01

Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. The calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10(6) protons/pulse and beam current.

Theoretical detection threshold of the proton-acoustic range verification technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmad, Moiz; Yousefi, Siavash; Xing, Lei, E-mail: lei@stanford.edu

2015-10-15

Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method.more » Various beam pulse widths (0.1–10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. Results: The calculated noise in the transducer was 12–28 mPa, depending on the transducer central frequency (70–380 kHz). The minimum number of protons detectable by the technique was on the order of 3–30 × 10{sup 6} per pulse, with 30–800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10{sup 6} protons/pulse and beam current.« less

Theoretical detection threshold of the proton-acoustic range verification technique

PubMed Central

Ahmad, Moiz; Xiang, Liangzhong; Yousefi, Siavash; Xing, Lei

2015-01-01

Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1–10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. Results: The calculated noise in the transducer was 12–28 mPa, depending on the transducer central frequency (70–380 kHz). The minimum number of protons detectable by the technique was on the order of 3–30 × 106 per pulse, with 30–800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 106 protons/pulse and beam current. PMID:26429247

Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI.

PubMed

Koush, Yury; Zvyagintsev, Mikhail; Dyck, Miriam; Mathiak, Krystyna A; Mathiak, Klaus

2012-01-02

Real-time fMRI allows analysis and visualization of the brain activity online, i.e. within one repetition time. It can be used in neurofeedback applications where subjects attempt to control an activation level in a specified region of interest (ROI) of their brain. The signal derived from the ROI is contaminated with noise and artifacts, namely with physiological noise from breathing and heart beat, scanner drift, motion-related artifacts and measurement noise. We developed a Bayesian approach to reduce noise and to remove artifacts in real-time using a modified Kalman filter. The system performs several signal processing operations: subtraction of constant and low-frequency signal components, spike removal and signal smoothing. Quantitative feedback signal quality analysis was used to estimate the quality of the neurofeedback time series and performance of the applied signal processing on different ROIs. The signal-to-noise ratio (SNR) across the entire time series and the group event-related SNR (eSNR) were significantly higher for the processed time series in comparison to the raw data. Applied signal processing improved the t-statistic increasing the significance of blood oxygen level-dependent (BOLD) signal changes. Accordingly, the contrast-to-noise ratio (CNR) of the feedback time series was improved as well. In addition, the data revealed increase of localized self-control across feedback sessions. The new signal processing approach provided reliable neurofeedback, performed precise artifacts removal, reduced noise, and required minimal manual adjustments of parameters. Advanced and fast online signal processing algorithms considerably increased the quality as well as the information content of the control signal which in turn resulted in higher contingency in the neurofeedback loop. Copyright © 2011 Elsevier Inc. All rights reserved.

49 CFR 218.22 - Utility employee.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.22 Utility... railroad rolling equipment must be provided with blue signal protection in accordance with §§ 218.23... provided blue signal protection in accordance with §§ 218.23 through 218.30 of this part. (h) Nothing in...

49 CFR 218.22 - Utility employee.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.22 Utility... railroad rolling equipment must be provided with blue signal protection in accordance with §§ 218.23... provided blue signal protection in accordance with §§ 218.23 through 218.30 of this part. (h) Nothing in...

EFQPSK Versus CERN: A Comparative Study

NASA Technical Reports Server (NTRS)

Borah, Deva K.; Horan, Stephen

2001-01-01

This report presents a comparative study on Enhanced Feher's Quadrature Phase Shift Keying (EFQPSK) and Constrained Envelope Root Nyquist (CERN) techniques. These two techniques have been developed in recent times to provide high spectral and power efficiencies under nonlinear amplifier environment. The purpose of this study is to gain insights into these techniques and to help system planners and designers with an appropriate set of guidelines for using these techniques. The comparative study presented in this report relies on effective simulation models and procedures. Therefore, a significant part of this report is devoted to understanding the mathematical and simulation models of the techniques and their set-up procedures. In particular, mathematical models of EFQPSK and CERN, effects of the sampling rate in discrete time signal representation, and modeling of nonlinear amplifiers and predistorters have been considered in detail. The results of this study show that both EFQPSK and CERN signals provide spectrally efficient communications compared to filtered conventional linear modulation techniques when a nonlinear power amplifier is used. However, there are important differences. The spectral efficiency of CERN signals, with a small amount of input backoff, is significantly better than that of EFQPSK signals if the nonlinear amplifier is an ideal clipper. However, to achieve such spectral efficiencies with a practical nonlinear amplifier, CERN processing requires a predistorter which effectively translates the amplifier's characteristics close to those of an ideal clipper. Thus, the spectral performance of CERN signals strongly depends on the predistorter. EFQPSK signals, on the other hand, do not need such predistorters since their spectra are almost unaffected by the nonlinear amplifier, Ibis report discusses several receiver structures for EFQPSK signals. It is observed that optimal receiver structures can be realized for both coded and uncoded EFQPSK signals with not too much increase in computational complexity. When a nonlinear amplifier is used, the bit error rate (BER) performance of the CERN signals with a matched filter receiver is found to be more than one decibel (dB) worse compared to the bit error performance of EFQPSK signals. Although channel coding is found to provide BER performance improvement for both EFQPSK and CERN signals, the performance of EFQPSK signals remains better than that of CERN. Optimal receiver structures for CERN signals with nonlinear equalization is left as a possible future work. Based on the numerical results, it is concluded that, in nonlinear channels, CERN processing leads towards better bandwidth efficiency with a compromise in power efficiency. Hence for bandwidth efficient communications needs, CERN is a good solution provided effective adaptive predistorters can be realized. On the other hand, EFQPSK signals provide a good power efficient solution with a compromise in band width efficiency.

On the influence of noise correlations in measurement data on basis image noise in dual-energylike x-ray imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roessl, Ewald; Ziegler, Andy; Proksa, Roland

2007-03-15

In conventional dual-energy systems, two transmission measurements with distinct spectral characteristics are performed. These measurements are used to obtain the line integrals of two basis material densities. Usually, the measurement process is such that the two measured signals can be treated as independent and therefore uncorrelated. Recently, however, a readout system for x-ray detectors has been introduced for which this is no longer the case. The readout electronics is designed to obtain simultaneous measurements of the total number of photons N and the total energy E they deposit in the sensor material. Practically, this is realized by a signal replicationmore » and separate counting and integrating processing units. Since the quantities N and E are (electronically) derived from one and the same physical sensor signal, they are statistically correlated. Nevertheless, the pair N and E can be used to perform a dual-energy processing following the well-known approach by Alvarez and Macovski. Formally, this means that N is to be identified with the first dual-energy measurement M{sub 1} and E with the second measurement M{sub 2}. In the presence of input correlations between M{sub 1}=N and M{sub 2}=E, however, the corresponding analytic expressions for the basis image noise have to be modified. The main observation made in this paper is that for positively correlated data, as is the case for the simultaneous counting and integrating device mentioned above, the basis image noise is suppressed through the influence of the covariance between the two signals. We extend the previously published relations for the basis image noise to the case where the original measurements are not independent and illustrate the importance of the input correlations by comparing dual-energy basis image noise resulting from the device mentioned above and a device measuring the photon numbers and the deposited energies consecutively.« less

Directional dual-tree rational-dilation complex wavelet transform.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2014-01-01

Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

DOE PAGES

Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.; ...

2016-09-22

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry,STIG),which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIGmore » method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as out perform traditional within-subject calibration techniques when limited data is available. Here, this method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.« less

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry,STIG),which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIGmore » method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as out perform traditional within-subject calibration techniques when limited data is available. Here, this method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.« less

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.

PubMed

He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P

2013-09-18

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Comparison of multichannel wide dynamic range compression and ChannelFree processing in open canal hearing instruments.

PubMed

Plyler, Patrick N; Reber, Monika Bertges; Kovach, Amanda; Galloway, Elisabeth; Humphrey, Elizabeth

2013-02-01

Multichannel wide dynamic range compression (WDRC) and ChannelFree processing have similar goals yet differ significantly in terms of signal processing. Multichannel WDRC devices divide the input signal into separate frequency bands; a separate level is determined within each frequency band; and compression in each band is based on the level within each band. ChannelFree processing detects the wideband level, and gain adjustments are based on the wideband signal level and adjusted up to 20,000 times per second. Although both signal processing strategies are currently available in hearing aids, it is unclear if differences in these signal processing strategies affect the performance and/or preference of the end user. The purpose of the research was to determine the effects of multichannel wide dynamic range compression and ChannelFree processing on performance and/or preference of listeners using open-canal hearing instruments. An experimental study in which subjects were exposed to a repeated measures design was utilized. Fourteen adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Participants completed two 5 wk trial periods for each signal processing strategy. Probe microphone, behavioral and subjective measures were conducted unaided and aided at the end of each trial period. Behavioral and subjective results for both signal processing strategies were significantly better than unaided results; however, behavioral and subjective results were not significantly different between the signal processing strategies. Multichannel WDRC and ChannelFree processing are both effective signal processing strategies that provide significant benefit for hearing instrument users. Overall preference between the strategies may be related to the degree of hearing loss of the user, high-frequency in-situ levels, and/or acceptance of background noise. American Academy of Audiology.

Evaluation of non-selective refocusing pulses for 7 T MRI

PubMed Central

Moore, Jay; Jankiewicz, Marcin; Anderson, Adam W.; Gore, John C.

2011-01-01

There is a continuing need for improved RF pulses that achieve proper refocusing in the context of ultra-high field (≥ 7 T) human MRI. Simple block or sinc pulses are highly susceptible to RF field inhomogeneities, and adiabatic pulses are generally considered too SAR intensive for practical use at 7 T. The performance of the array of pulses falling between these extremes, however, has not been systematically evaluated. The aim of this work was to compare the performances of 21 non-selective refocusing pulses spanning a range of durations and SAR levels. The evaluation was based upon simulations and both phantom and in vivo human brain experiments conducted at 7 T. Tested refocusing designs included block, composite block, BIR-4, hyperbolic secant, and numerically optimized composite waveforms. These pulses were divided into three SAR classes and two duration categories, and, based on signal gain in a 3-D spin echo sequence, practical recommendations on usage are made within each category. All evaluated pulses were found to produce greater volume-averaged signals relative to a 180° block pulse. Although signal gains often come with the price of increased SAR or duration, some pulses were found to result in significant signal enhancement while also adhering to practical constraints. This work demonstrates the signal gains and losses realizable with single-channel refocusing pulse designs and should assist in the selection of suitable refocusing pulses for practical 3-D spin-echo imaging at 7 T. It further establishes a reference against which future pulses and multi-channel designs can be compared. PMID:22177384

A metrics for soil hydrological processes and their intrinsic dimensionality in heterogeneous systems

NASA Astrophysics Data System (ADS)

Lischeid, G.; Hohenbrink, T.; Schindler, U.

2012-04-01

Hydrology is based on the observation that catchments process input signals, e.g., precipitation, in a highly deterministic way. Thus, the Darcy or the Richards equation can be applied to model water fluxes in the saturated or vadose zone, respectively. Soils and aquifers usually exhibit substantial spatial heterogeneities at different scales that can, in principle, be represented by corresponding parameterisations of the models. In practice, however, data are hardly available at the required spatial resolution, and accounting for observed heterogeneities of soil and aquifer structure renders models very time and CPU consuming. We hypothesize that the intrinsic dimensionality of soil hydrological processes, which is induced by spatial heterogeneities, actually is very low and that soil hydrological processes in heterogeneous soils follow approximately the same trajectory. That means, the way how the soil transforms any hydrological input signals is the same for different soil textures and structures. Different soils differ only with respect to the extent of transformation of input signals. In a first step, we analysed the output of a soil hydrological model, based on the Richards equation, for homogeneous soils down to 5 m depth for different soil textures. A matrix of time series of soil matrix potential and soil water content at 10 cm depth intervals was set up. The intrinsic dimensionality of that matrix was assessed using the Correlation Dimension and a non-linear principal component approach. The latter provided a metrics for the extent of transformation ("damping") of the input signal. In a second step, model outputs for heterogeneous soils were analysed. In a last step, the same approaches were applied to 55 time series of observed soil water content from 15 sites and different depths. In all cases, the intrinsic dimensionality in fact was very close to unity, confirming our hypothesis. The metrics provided a very efficient tool to quantify the observed behaviour, depending on depth and soil heterogeneity: Different soils differed primarily with respect to the extent of damping per depth interval rather than to the kind of damping. We will show how that metrics can be used in a very efficient way for representing soil heterogeneities in simulation models.

Multichannel heterodyning for wideband interferometry, correlation and signal processing

DOEpatents

Erskine, David J.

1999-01-01

A method of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized.

Multichannel heterodyning for wideband interferometry, correlation and signal processing

DOEpatents

Erskine, D.J.

1999-08-24

A method is disclosed of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized. 50 figs.

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

[Prescribing monitoring in clinical practice: from enlightened empiricism to rational strategies].

PubMed

Buclin, Thierry; Herzig, Lilli

2013-05-15

Monitoring of a medical condition is the periodic measurement of one or several physiological or biological variables to detect a signal regarding its clinical progression or its response to treatment. We distinguish different medical situations between diagnostic, clinical and therapeutic process to apply monitoring. Many clinical, variables can be used for monitoring, once their intrinsic properties (normal range, critical difference, kinetics, reactivity) and external validity (pathophysiological importance, predictive power for clinical outcomes) are established. A formal conceptualization of monitoring is being developed and should support the rational development of monitoring strategies and their validation through appropriate clinical trials.

Dental technology over 150 years: evolution and revolution.

PubMed

Feuerstein, Paul

2014-01-01

A patient entering a dental office is often greeted and then checked in through the practice management system's digital appointment book. The provider is notified by an electronic signal that is visual, audible, or both. The patient is led to the treatment area and sits in a dental chair which is adjusted to the individual's size and position for the treatment, and the light is positioned. Sometimes a radiograph is taken, local anesthetic is delivered, and a handpiece--air turbine or electric--is used for the procedure. How different is this process today from a dentist treating a patient in 1864?

A Tutorial on Creating a Grid Cell Land Cover Data File from Remote Sensing Data.

DTIC Science & Technology

1985-06-01

Creating a Grid Cell Land Cover Data File from Remote Sensing Data Gary E. Ford, Doreen L Meyer, and V. Ralph Algazi Signal and Image Processing Laboratory... L 1. INTRODUCTION Spatial data management systems, also known as geographic information systems, pro- vide powerful, practical tools for the...erosion [8]. Other -... ..... .. . . .. . . -5- 60 Z 0"C. 0 0. , ...- 9L> c 0 o o ( L - 0- 0.0a c 0 4- b. 0 ~ CL*~ C 0 .CL x 0 I" .- -J oo : -. 0 a a Z 0Z I1

Charge Coupled Devices in Signal Processing Systems. Volume V. Final Report.

DTIC Science & Technology

1979-12-01

the Phase III program. At that time, mutual customer /contractor interest arose in a unique application area, involving manipulation of lists of...using half adders and "or" circuits. 4-35 3 b 2 b3 01 b *3b, *2 b 1 b2b 1 0 1 b, + + + + + + ++ r T 7 7 r* 7FA +-0j FA 147 7 7 1 77 7 7 TL NO.6 NO. 5...which the cell could be step-and- repeated into an array in the CAD system. In practice we found that the attendent custom skewing delay layout

Real-time processing of EMG signals for bionic arm purposes

NASA Astrophysics Data System (ADS)

Olid Dominguez, Ferran; Wawrzyniak, Zbigniew M.

2016-09-01

This paper is connected with the problem of prostheses, that have always been a necessity for the human being. Bio-physiological signals from muscles, electromyographic signals have been collected, analyzed and processed in order to implement a real-time algorithm which is capable of differentiation of two different states of a bionic hand: open and closed. An algorithm for real-time electromyographic signal processing with almost no false positives is presented and it is explained that in bio-physiological experiments proper signal processing is of great importance.

Intelligent Signal Processing for Active Control

DTIC Science & Technology

1992-06-17

FUNDING NUMSI Intelligent Signal Processing for Active Control C-NO001489-J-1633 G. AUTHOR(S) P.A. Ramamoorthy 7. P2RFORMING ORGANIZATION NAME(S) AND...unclassified .unclassified unclassified L . I mu-. W UNIVERSITY OF CINCINNATI COLLEGE OF ENGINEERING Intelligent Signal Processing For Rctiue Control...NAURI RESEARCH Conkact No: NO1489-J-1633 P.L: P.A.imoodh Intelligent Signal Processing For Active Control 1 Executive Summary The thrust of this

Standardization of pitch-range settings in voice acoustic analysis.

PubMed

Vogel, Adam P; Maruff, Paul; Snyder, Peter J; Mundt, James C

2009-05-01

Voice acoustic analysis is typically a labor-intensive, time-consuming process that requires the application of idiosyncratic parameters tailored to individual aspects of the speech signal. Such processes limit the efficiency and utility of voice analysis in clinical practice as well as in applied research and development. In the present study, we analyzed 1,120 voice files, using standard techniques (case-by-case hand analysis), taking roughly 10 work weeks of personnel time to complete. The results were compared with the analytic output of several automated analysis scripts that made use of preset pitch-range parameters. After pitch windows were selected to appropriately account for sex differences, the automated analysis scripts reduced processing time of the 1,120 speech samples to less than 2.5 h and produced results comparable to those obtained with hand analysis. However, caution should be exercised when applying the suggested preset values to pathological voice populations.

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

[Early mother-infant interaction and factors negatively affecting parenting].

PubMed

Cerezo, María Angeles; Trenado, Rosa María; Pons-Salvador, Gemma

2006-08-01

The social information-processing model contributes to identifying the psychological processes underlying the construct "sensitivity" in early mother-child interaction. Negative emotional states associated with inadequate self-regulation in coping with stressors affect the mother's attention skills and the processing of the baby's signals. This leads to less synchronous parental practices, particularly unsatisfactory when the baby is unhappy, or crying because the required self-regulation is not provided. This micro-social research studies the sequential profile of maternal reactions to the baby's positive/neutral vs. difficult behaviours and compares them in two groups of dyads, one with mothers who reported high levels of distress and other negative factors for parenting and another group with low levels. The unfavourable circumstances of the high stress group and their negative effects on interaction were observed in some indiscriminate maternal responses and particularly as they reacted to their baby's difficult behaviour, when the mother's regulatory role is more necessary.

49 CFR 218.24 - One-person crew.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.24 One... between rolling equipment, without blue signal protection that complies with § 218.27 or § 218.29, unless...

49 CFR 218.24 - One-person crew.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.24 One... between rolling equipment, without blue signal protection that complies with § 218.27 or § 218.29, unless...

49 CFR 218.24 - One-person crew.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.24 One... between rolling equipment, without blue signal protection that complies with § 218.27 or § 218.29, unless...

49 CFR 218.24 - One-person crew.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.24 One... between rolling equipment, without blue signal protection that complies with § 218.27 or § 218.29, unless...

49 CFR 218.24 - One-person crew.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218.24 One... between rolling equipment, without blue signal protection that complies with § 218.27 or § 218.29, unless...

49 CFR 218.27 - Workers on track other than main track.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218... on track other than main track— (a) A blue signal must be displayed at or near each manually operated... blue signal protection as provided for in this section is on a track equipped with one or more...

49 CFR 218.27 - Workers on track other than main track.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218... on track other than main track— (a) A blue signal must be displayed at or near each manually operated... blue signal protection as provided for in this section is on a track equipped with one or more...

49 CFR 218.27 - Workers on track other than main track.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218... on track other than main track— (a) A blue signal must be displayed at or near each manually operated... blue signal protection as provided for in this section is on a track equipped with one or more...

49 CFR 218.27 - Workers on track other than main track.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218... on track other than main track— (a) A blue signal must be displayed at or near each manually operated... blue signal protection as provided for in this section is on a track equipped with one or more...

49 CFR 218.27 - Workers on track other than main track.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Blue Signal Protection of Workers § 218... on track other than main track— (a) A blue signal must be displayed at or near each manually operated... blue signal protection as provided for in this section is on a track equipped with one or more...

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, Craig L.; Oma, Kenton H.; Davis, Karl C.

1988-01-01

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, C.L.; Oma, K.H.; Davis, K.C.

1988-08-09

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process. 7 figs.

Wavelet-Based Peak Detection and a New Charge Inference Procedure for MS/MS Implemented in ProteoWizard’s msConvert

PubMed Central

2015-01-01

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1–100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets. PMID:25411686

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert.

PubMed

French, William R; Zimmerman, Lisa J; Schilling, Birgit; Gibson, Bradford W; Miller, Christine A; Townsend, R Reid; Sherrod, Stacy D; Goodwin, Cody R; McLean, John A; Tabb, David L

2015-02-06

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1-100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.

Increasing cell-device adherence using cultured insect cells for receptor-based biosensors

NASA Astrophysics Data System (ADS)

Terutsuki, Daigo; Mitsuno, Hidefumi; Sakurai, Takeshi; Okamoto, Yuki; Tixier-Mita, Agnès; Toshiyoshi, Hiroshi; Mita, Yoshio; Kanzaki, Ryohei

2018-03-01

Field-effect transistor (FET)-based biosensors have a wide range of applications, and a bio-FET odorant sensor, based on insect (Sf21) cells expressing insect odorant receptors (ORs) with sensitivity and selectivity, has emerged. To fully realize the practical application of bio-FET odorant sensors, knowledge of the cell-device interface for efficient signal transfer, and a reliable and low-cost measurement system using the commercial complementary metal-oxide semiconductor (CMOS) foundry process, will be indispensable. However, the interfaces between Sf21 cells and sensor devices are largely unknown, and electrode materials used in the commercial CMOS foundry process are generally limited to aluminium, which is reportedly toxic to cells. In this study, we investigated Sf21 cell-device interfaces by developing cross-sectional specimens. Calcium imaging of Sf21 cells expressing insect ORs was used to verify the functions of Sf21 cells as odorant sensor elements on the electrode materials. We found that the cell-device interface was approximately 10 nm wide on average, suggesting that the adhesion mechanism of Sf21 cells may differ from that of other cells. These results will help to construct accurate signal detection from expressed insect ORs using FETs.

Covariance NMR Processing and Analysis for Protein Assignment.

PubMed

Harden, Bradley J; Frueh, Dominique P

2018-01-01

During NMR resonance assignment it is often necessary to relate nuclei to one another indirectly, through their common correlations to other nuclei. Covariance NMR has emerged as a powerful technique to correlate such nuclei without relying on error-prone peak peaking. However, false-positive artifacts in covariance spectra have impeded a general application to proteins. We recently introduced pre- and postprocessing steps to reduce the prevalence of artifacts in covariance spectra, allowing for the calculation of a variety of 4D covariance maps obtained from diverse combinations of pairs of 3D spectra, and we have employed them to assign backbone and sidechain resonances in two large and challenging proteins. In this chapter, we present a detailed protocol describing how to (1) properly prepare existing 3D spectra for covariance, (2) understand and apply our processing script, and (3) navigate and interpret the resulting 4D spectra. We also provide solutions to a number of errors that may occur when using our script, and we offer practical advice when assigning difficult signals. We believe such 4D spectra, and covariance NMR in general, can play an integral role in the assignment of NMR signals.

Impairments Computation for Routing Purposes in a Transparent-Access Optical Network Based on Optical CDMA and WDM

NASA Astrophysics Data System (ADS)

Musa, Ahmed

2016-06-01

Optical access networks are becoming more widespread and the use of multiple services might require a transparent optical network (TON). Multiplexing and privacy could benefit from the combination of wavelength division multiplexing (WDM) and optical coding (OC) and wavelength conversion in optical switches. The routing process needs to be cognizant of different resource types and characteristics such as fiber types, fiber linear impairments such as attenuation, dispersion, etc. as well as fiber nonlinear impairments such as four-wave mixing, cross-phase modulation, etc. Other types of impairments, generated by optical nodes or photonic switches, also affect the signal quality (Q) or the optical signal to noise ratio (OSNR), which is related to the bit error rate (BER). Therefore, both link and switch impairments must be addressed and somehow incorporated into the routing algorithm. However, it is not practical to fully integrate all photonic-specific attributes in the routing process. In this study, new routing parameters and constraints are defined that reflect the distinct characteristics of photonic networking. These constraints are applied to the design phase of TON and expressed as a cost or metric form that will be used in the network routing algorithm.

Increasing cell–device adherence using cultured insect cells for receptor-based biosensors

PubMed Central

Mitsuno, Hidefumi; Sakurai, Takeshi; Okamoto, Yuki; Tixier-Mita, Agnès; Toshiyoshi, Hiroshi; Mita, Yoshio; Kanzaki, Ryohei

2018-01-01

Field-effect transistor (FET)-based biosensors have a wide range of applications, and a bio-FET odorant sensor, based on insect (Sf21) cells expressing insect odorant receptors (ORs) with sensitivity and selectivity, has emerged. To fully realize the practical application of bio-FET odorant sensors, knowledge of the cell–device interface for efficient signal transfer, and a reliable and low-cost measurement system using the commercial complementary metal-oxide semiconductor (CMOS) foundry process, will be indispensable. However, the interfaces between Sf21 cells and sensor devices are largely unknown, and electrode materials used in the commercial CMOS foundry process are generally limited to aluminium, which is reportedly toxic to cells. In this study, we investigated Sf21 cell–device interfaces by developing cross-sectional specimens. Calcium imaging of Sf21 cells expressing insect ORs was used to verify the functions of Sf21 cells as odorant sensor elements on the electrode materials. We found that the cell–device interface was approximately 10 nm wide on average, suggesting that the adhesion mechanism of Sf21 cells may differ from that of other cells. These results will help to construct accurate signal detection from expressed insect ORs using FETs. PMID:29657822

All-optical universal logic gates on nonlinear multimode interference coupler using tunable input intensity

NASA Astrophysics Data System (ADS)

Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

2015-04-01

The theory of Nonlinear Modal Propagation Analysis Method (NMPA) have shown significant features of nonlinear multimode interference (MMI) coupler with compact dimension and when launched near the threshold of nonlinearity. Moreover, NMPA have the potential to allow studying the nonlinear MMI based the modal interference to explorer the phenomenon that what happen due to the natural of multimode region. Proposal of all-optical switch based NMPA has approved its capability to achieving the all-optical gates. All-optical gates have attracted increasing attention due to their practical utility in all-optical signal processing networks and systems. Nonlinear multimode interference devices could apply as universal all-optical gates due to significant features that NMPA introduce them. In this Paper, we present a novel Ultra-compact MMI coupler based on NMPA method in low intensity compared to last reports either as a novel design method and potential application for optical NAND, NOR as universal gates on single structure for Boolean logic signal processing devices and optimize their application via studding the contrast ratio between ON and OFF as a function of output width. We have applied NMPA for several applications so that the miniaturization in low nonlinear intensities is their main purpose.

Filter bank common spatial patterns in mental workload estimation.

PubMed

Arvaneh, Mahnaz; Umilta, Alberto; Robertson, Ian H

2015-01-01

EEG-based workload estimation technology provides a real time means of assessing mental workload. Such technology can effectively enhance the performance of the human-machine interaction and the learning process. When designing workload estimation algorithms, a crucial signal processing component is the feature extraction step. Despite several studies on this field, the spatial properties of the EEG signals were mostly neglected. Since EEG inherently has a poor spacial resolution, features extracted individually from each EEG channel may not be sufficiently efficient. This problem becomes more pronounced when we use low-cost but convenient EEG sensors with limited stability which is the case in practical scenarios. To address this issue, in this paper, we introduce a filter bank common spatial patterns algorithm combined with a feature selection method to extract spatio-spectral features discriminating different mental workload levels. To evaluate the proposed algorithm, we carry out a comparative analysis between two representative types of working memory tasks using data recorded from an Emotiv EPOC headset which is a mobile low-cost EEG recording device. The experimental results showed that the proposed spatial filtering algorithm outperformed the state-of-the algorithms in terms of the classification accuracy.

Model-based damage evaluation of layered CFRP structures

NASA Astrophysics Data System (ADS)

Munoz, Rafael; Bochud, Nicolas; Rus, Guillermo; Peralta, Laura; Melchor, Juan; Chiachío, Juan; Chiachío, Manuel; Bond, Leonard J.

2015-03-01

An ultrasonic evaluation technique for damage identification of layered CFRP structures is presented. This approach relies on a model-based estimation procedure that combines experimental data and simulation of ultrasonic damage-propagation interactions. The CFPR structure, a [0/90]4s lay-up, has been tested in an immersion through transmission experiment, where a scan has been performed on a damaged specimen. Most ultrasonic techniques in industrial practice consider only a few features of the received signals, namely, time of flight, amplitude, attenuation, frequency contents, and so forth. In this case, once signals are captured, an algorithm is used to reconstruct the complete signal waveform and extract the unknown damage parameters by means of modeling procedures. A linear version of the data processing has been performed, where only Young modulus has been monitored and, in a second nonlinear version, the first order nonlinear coefficient β was incorporated to test the possibility of detection of early damage. The aforementioned physical simulation models are solved by the Transfer Matrix formalism, which has been extended from linear to nonlinear harmonic generation technique. The damage parameter search strategy is based on minimizing the mismatch between the captured and simulated signals in the time domain in an automated way using Genetic Algorithms. Processing all scanned locations, a C-scan of the parameter of each layer can be reconstructed, obtaining the information describing the state of each layer and each interface. Damage can be located and quantified in terms of changes in the selected parameter with a measurable extension. In the case of the nonlinear coefficient of first order, evidence of higher sensitivity to damage than imaging the linearly estimated Young Modulus is provided.

Frequency domain laser velocimeter signal processor: A new signal processing scheme

NASA Technical Reports Server (NTRS)

Meyers, James F.; Clemmons, James I., Jr.

1987-01-01

A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

On the Road to Translation for PTSD Treatment: Theoretical and Practical Considerations of the Use of Human Models of Conditioned Fear for Drug Development.

PubMed

Risbrough, Victoria B; Glenn, Daniel E; Baker, Dewleen G

The use of quantitative, laboratory-based measures of threat in humans for proof-of-concept studies and target development for novel drug discovery has grown tremendously in the last 2 decades. In particular, in the field of posttraumatic stress disorder (PTSD), human models of fear conditioning have been critical in shaping our theoretical understanding of fear processes and importantly, validating findings from animal models of the neural substrates and signaling pathways required for these complex processes. Here, we will review the use of laboratory-based measures of fear processes in humans including cued and contextual conditioning, generalization, extinction, reconsolidation, and reinstatement to develop novel drug treatments for PTSD. We will primarily focus on recent advances in using behavioral and physiological measures of fear, discussing their sensitivity as biobehavioral markers of PTSD symptoms, their response to known and novel PTSD treatments, and in the case of d-cycloserine, how well these findings have translated to outcomes in clinical trials. We will highlight some gaps in the literature and needs for future research, discuss benefits and limitations of these outcome measures in designing proof-of-concept trials, and offer practical guidelines on design and interpretation when using these fear models for drug discovery.

Novel sonar signal processing tool using Shannon entropy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quazi, A.H.

1996-06-01

Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will bemore » based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}« less

A fully reconfigurable photonic integrated signal processor

NASA Astrophysics Data System (ADS)

Liu, Weilin; Li, Ming; Guzzon, Robert S.; Norberg, Erik J.; Parker, John S.; Lu, Mingzhi; Coldren, Larry A.; Yao, Jianping

2016-03-01

Photonic signal processing has been considered a solution to overcome the inherent electronic speed limitations. Over the past few years, an impressive range of photonic integrated signal processors have been proposed, but they usually offer limited reconfigurability, a feature highly needed for the implementation of large-scale general-purpose photonic signal processors. Here, we report and experimentally demonstrate a fully reconfigurable photonic integrated signal processor based on an InP-InGaAsP material system. The proposed photonic signal processor is capable of performing reconfigurable signal processing functions including temporal integration, temporal differentiation and Hilbert transformation. The reconfigurability is achieved by controlling the injection currents to the active components of the signal processor. Our demonstration suggests great potential for chip-scale fully programmable all-optical signal processing.

User's manual SIG: a general-purpose signal processing program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lager, D.; Azevedo, S.

1983-10-25

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Many of the basic operations one would perform on digitized data are contained in the core SIG package. Out of these core commands, more powerful signal processing algorithms may be built. Many different operations on time- and frequency-domain signals can be performed by SIG. They include operations on the samples of a signal, such as adding a scalar tomore » each sample, operations on the entire signal such as digital filtering, and operations on two or more signals such as adding two signals. Signals may be simulated, such as a pulse train or a random waveform. Graphics operations display signals and spectra.« less

Ferroelectric domain engineering by focused infrared femtosecond pulses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xin; Shvedov, Vladlen; Sheng, Yan, E-mail: yan.sheng@anu.edu.au

2015-10-05

We demonstrate infrared femtosecond laser-induced inversion of ferroelectric domains. This process can be realised solely by using tightly focused laser pulses without application of any electric field prior to, in conjunction with, or subsequent to the laser irradiation. As most ferroelectric crystals like LiNbO{sub 3}, LiTaO{sub 3}, and KTiOPO{sub 4} are transparent in the infrared, this optical poling method allows one to form ferroelectric domain patterns much deeper inside a ferroelectric crystal than by using ultraviolet light and hence can be used to fabricate practical devices. We also propose in situ diagnostics of the ferroelectric domain inversion process by monitoringmore » the Čerenkov second harmonic signal, which is sensitive to the appearance of ferroelectric domain walls.« less

Hydraulophones: Acoustic musical instruments and expressive user interfaces

NASA Astrophysics Data System (ADS)

Janzen, Ryan E.

Fluid flow creates an expansive range of acoustic possibilities, particularly in the case of water, which has unique turbulence and vortex shedding properties as compared with the air of ordinary wind instruments. Sound from water flow is explained with reference to a new class of musical instruments, hydraulophones, in which oscillation originates directly from matter in its liquid state. Several hydraulophones which were realized in practical form are described. A unique user-interface consisting of a row of water jets is presented, in terms of its expressiveness, tactility, responsiveness to derivatives and integrals of displacement, and in terms of the direct physical interaction between a user and the physical process of sound production. Signal processing algorithms are introduced, which extract further information from turbulent water flow, for industrial applications as well as musical applications.

Comparison of the results of refractometric measurements in the process of diffusion, obtained by means of the backgroundoriented schlieren method and the holographic interferometry method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraiskii, A V; Mironova, T V

2015-08-31

The results of the study of interdiffusion of two liquids, obtained using the holographic recording scheme with a nonstationary reference wave with the frequency linearly varying in space and time are compared with the results of correlation processing of digital photographs, made with a random background screen. The spatio-temporal behaviour of the signal in four basic representations ('space – temporal frequency', 'space – time', 'spatial frequency – temporal frequency' and 'spatial frequency – time') is found in the holographic experiment and calculated (in the appropriate coordinates) based on the background-oriented schlieren method. Practical coincidence of the results of the correlationmore » analysis and the holographic double-exposure interferometry is demonstrated. (interferometry)« less

Spinning Disk Confocal Imaging of Neutrophil Migration in Zebrafish

PubMed Central

Lam, Pui-ying; Fischer, Robert S; Shin, William D.; Waterman, Clare M; Huttenlocher, Anna

2014-01-01

Live-cell imaging techniques have been substantially improved due to advances in confocal microscopy instrumentation coupled with ultrasensitive detectors. The spinning disk confocal system is capable of generating images of fluorescent live samples with broad dynamic range and high temporal and spatial resolution. The ability to acquire fluorescent images of living cells in vivo on a millisecond timescale allows the dissection of biological processes that have not previously been visualized in a physiologically relevant context. In vivo imaging of rapidly moving cells such as neutrophils can be technically challenging. In this chapter, we describe the practical aspects of imaging neutrophils in zebrafish embryos using spinning disk confocal microscopy. Similar setups can also be applied to image other motile cell types and signaling processes in translucent animals or tissues. PMID:24504955

Generalized Parameter-Adjusted Stochastic Resonance of Duffing Oscillator and Its Application to Weak-Signal Detection.

PubMed

Lai, Zhi-Hui; Leng, Yong-Gang

2015-08-28

A two-dimensional Duffing oscillator which can produce stochastic resonance (SR) is studied in this paper. We introduce its SR mechanism and present a generalized parameter-adjusted SR (GPASR) model of this oscillator for the necessity of parameter adjustments. The Kramers rate is chosen as the theoretical basis to establish a judgmental function for judging the occurrence of SR in this model; and to analyze and summarize the parameter-adjusted rules under unmatched signal amplitude, frequency, and/or noise-intensity. Furthermore, we propose the weak-signal detection approach based on this GPASR model. Finally, we employ two practical examples to demonstrate the feasibility of the proposed approach in practical engineering application.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Microwave signal processing with photorefractive dynamic holography

NASA Astrophysics Data System (ADS)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that of a regular 50 W household light bulb. The system was shipped to different parts of the country for real-time demonstrations of signal separation thus also validating its claim to robustness.

Gas turbine engine control system

NASA Technical Reports Server (NTRS)

Idelchik, Michael S. (Inventor)

1991-01-01

A control system and method of controlling a gas turbine engine. The control system receives an error signal and processes the error signal to form a primary fuel control signal. The control system also receives at least one anticipatory demand signal and processes the signal to form an anticipatory fuel control signal. The control system adjusts the value of the anticipatory fuel control signal based on the value of the error signal to form an adjusted anticipatory signal and then the adjusted anticipatory fuel control signal and the primary fuel control signal are combined to form a fuel command signal.

Electronic filters, signal conversion apparatus, hearing aids and methods

NASA Technical Reports Server (NTRS)

Morley, Jr., Robert E. (Inventor); Engebretson, A. Maynard (Inventor); Engel, George L. (Inventor); Sullivan, Thomas J. (Inventor)

1994-01-01

An electronic filter for filtering an electrical signal. Signal processing circuitry therein includes a logarithmic filter having a series of filter stages with inputs and outputs in cascade and respective circuits associated with the filter stages for storing electrical representations of filter parameters. The filter stages include circuits for respectively adding the electrical representations of the filter parameters to the electrical signal to be filtered thereby producing a set of filter sum signals. At least one of the filter stages includes circuitry for producing a filter signal in substantially logarithmic form at its output by combining a filter sum signal for that filter stage with a signal from an output of another filter stage. The signal processing circuitry produces an intermediate output signal, and a multiplexer connected to the signal processing circuit multiplexes the intermediate output signal with the electrical signal to be filtered so that the logarithmic filter operates as both a logarithmic prefilter and a logarithmic postfilter. Other electronic filters, signal conversion apparatus, electroacoustic systems, hearing aids and methods are also disclosed.

Classification of Movement and Inhibition Using a Hybrid BCI.

PubMed

Chmura, Jennifer; Rosing, Joshua; Collazos, Steven; Goodwin, Shikha J

2017-01-01

Brain-computer interfaces (BCIs) are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI)-when a person imagines a motion without executing it-is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg) and characteristics (reaching vs. grabbing); and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR) motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows) and have solved this problem to an extent. Hybrid BCIs (hBCIs) implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs). These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside laboratory environments for motor rehabilitation in hospitals, and potentially for controlling a prosthetic.

Classification of Movement and Inhibition Using a Hybrid BCI

PubMed Central

Chmura, Jennifer; Rosing, Joshua; Collazos, Steven; Goodwin, Shikha J.

2017-01-01

Brain-computer interfaces (BCIs) are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI)—when a person imagines a motion without executing it—is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg) and characteristics (reaching vs. grabbing); and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR) motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows) and have solved this problem to an extent. Hybrid BCIs (hBCIs) implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs). These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside laboratory environments for motor rehabilitation in hospitals, and potentially for controlling a prosthetic. PMID:28860986

Analysis of Multipath Pixels in SAR Images

NASA Astrophysics Data System (ADS)

Zhao, J. W.; Wu, J. C.; Ding, X. L.; Zhang, L.; Hu, F. M.

2016-06-01

As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings) and the physical parameters of the surface (roughness, correlation length, permittivity)which determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.